SELECTION OF OPTIMAL INVESTMENT STRITEGIES
FOR LOW VOLUME ROADS
by
MARK ARNOLD BECKER
SB, Massachusetts Institute of Technology
Submitted in partial fulfillment
of the requirements for the degree of
Master of Science
at the
Massachusetts Institute of Technology
June, 1972
Signature ofAuthor ................
•.•.....•••....
Department of Civil Engineering
March 17,1972
Certified by......
......
T...
.
Thesis Super isor
Accepted by.. ........................... ...........
Chairman, Departmental Committee on
Graduate Students of the Department
of Civil Engineering
ABSTRACT
SELECTION OF OPTIMAL INVESTMENT STRATEGIES
FOR LOW VOLUIME ROADS
by
MARK ARNOLD BECKER
Submitted to the Department of Civil Engineering on
February 20, 1972,
in partial fulfillment of the requirements for the degree of Master of Science.
This thesis presents the Highway
Cost Model, a set of twenty computer routines written-in FORTRAN
IV which model the behavior of low
volume road investments over time.
The model was designed to be a tool
with which planners in developing
nations could locate those road projects which would provide optimal
return on scarce and constrained
resources. The HCM can consider uncertainty in traffic projections,
labor versus capital intensive maintenance and changes in factor prices
over time.
Thesis Supervisor:
Fred Moavenzadeh
Title:
Associate Professor
Acknowledgments
I would like to thank my wife, Deborah,
for her
advice, encouragement hard work and much, much more.
I would also like to thank Thomas Parody for
his work with the cost estimating routines and Louis
Berger, Inc.
who provided me with essential data
out which this thesis could not have been written.
Last, I would like to thank Fred Moavenzadeh
for his support and advice.
with-
CONTENTS
I.
II.
III.
IV.
V.
VI.
Title Page
Abstract
2
Acknowledgment
3
Table of Contents
4
Chapter One: Introduction
11
1. Maximizing Value: Modes of Approach
12
2.
Problems of Staged Construction
14
3.
Economic Issues in Staging
14
4. Use of Staged Construction in Project and
Systems Analysis
17
5.
18
Determining Optimal Staging Strategies
Chapter Two: Review of Literature
1. Staging Techniques
20
20
Specific Highway
2.
Staged Construction:
Techniques
3.
Staged Construction as Practiced in
Developing Nations
24
4.
Staged Construction: Pavement Design
29
5.
Empirical Models
29
6.
Mathematical Models for Staging
33.
7.
Facets of the Problem: The Timing Issue
33
8..
The Design Issue
35
9. Budget Constraints
22
36
10.
Staging Under Uncertainty
37
11.
Summary
37
VII.
VIII.
IX.
Chapter Three: Developing the HCM
39
1. The Basis: Cost Estimating Routines
39
2.
Developing the HCMM
41
3.
Selecting an Approach: The Alternatives
43
48
Chapter Four: The Computer Routines
1. The Staging Routines
48
2. Relationship to Cost Estimating Routines
63
3.
68
The Highway Cost Model Flowchart
Chaoter Five: Exxreriments in Staged Con-
74
struction: Techniques and Results
1. The Experiments
74
2.
The Scenarios
77
3.
Expanding the Parameters
78
4.
Elasticity of Demand
79
5.
Growth Rate
83
6.
Maintenance Policies
84
7.
Discount Rates
91
8.
Foreign Exchange
94
9.
Length of the Analysis Horizon
96
10.
Results of the Experiments:
Rules
The Pruning
100
11.
Rules for Flat Terrain
102
12.
Mountainous Terrain
102
13.
Maintenance
104
14.
Pruning Rules: Other Issues
105
Page
15.
X.
The Use of the Pruning Rules
Chapter Six: Use of the HCM
1. Data Collection
XIII.
107
Construction-Related Data
109
3.
Maintenance-Related Data
111
4. Data Related to User Operating Costs
112
5. Development and Selection of Staging
Alternatives
116
6.
Timing
117
7.
Upgradings
118
119
Search for the Optimal Road
121
10.
Continuing the Iteration
127
11.
Length of the Analysis Period
127
12.
Effects of Uncertainty in Traffic
Projections
130
13.
Effects on Total Costs
14.
Initial Traffic Levels
15.
Effects on the Optimal Strategy
16.
Road User Benefits
9.
XII.
107
2.
8. Maintenance
XI.
106
131
135
136
138
140
Chapter Seven: Conclusion
Bibliography
144
Appendices
150
A.
Recommendations for Further Work
151
B,
Willingness to Pay
153
Page
C.
Argentina and Bolivia Data
158
D.
The Earthwork Models
163
E.
Listing of the Highway Cost Model
166
LIST OF FIGURES
Number
Title
Page
1
Costs of Staged vs. Unstaged Construction
25
2
Flowchart for MAIN
50
3
Flowchart for STRAT
53
4
Flowchart for NETWRK
55
5
Flowchart for SAVDAT
62
6
Flowchart for CONSTR
64
7
Calling Sequences
67
8
Macro Flowchart for the HCM
69
9
The Staging Strategies
76
11
Argentina: Costs of Normal + High Elastic Traffic
82
Argentina: Costs of High + Normal Traffic Growth
12
Per kilometer operating costs vs. Maintenance
88
13
Maintenance Policy vs. Velocity
89
14
15
Maintenance Cost of Asphalt + Surface Treated
Roads
Advantages of Staged Construction
90
92
16
Effect of Interest Rates on Total Costs
93
17
Foreign Exchange Requirements--Low Traffic
97
18
Foreign Exchange Requirements--Normal Traffic
98
19
Foreign Exchange Requirements--High Traffic
99
20
Bolivia: Costs of Staged and UnStaged Roads
101
21
Map of Sapecho-Puerto Salinas Route
108
22
Bolivia Base Scenario Echo Print
114
23
Costs of the first Iteration
124
10
85
Title
Number
24 Staging Strategies for the Second Iteration
Page
125
25
Costs of the Second Iteration
126
26
Costs of the Third Iteration
128
27
Action of the Communication Model
141
28
Definition of Willingness to pay
154
29
Argentine Base Data
159
30
Bolivia Base Data
161
LIST OF TABLES
Number
Title
Page
1 Traffic Conditions used with Bolivia Data
80
2
Traffic Conditions used with Argentina Data
81
3
Labor and Capital Intensive Maintenance Policies
86
4
Foreign Exchange Component of Costs
95
5
Base Traffic for Bolivia Case Study
122
6
Effects of Inaccurate Growth Rates
132
7
Vehicles in Year 20 for two demand elasticities
134
Chapter One
Introduction
The lack of adequate transportation in many developing
countries has been cited by Haefele (48), Soberman (58), and
Steiner (42), among others, as one of the factors slowing
down the rate of industrialization and general economic development in those countries.
Transportation brings raw
materials to factories, workers to jobs, finished goods to
market, food to urban areas, and health and educational
services to the outlying population in much the same way
that arteries move vital resources through the human body,
thus making possible a complexity of function far beyond the
capacity of any single isolated organ.
It is clear that an
underdeveloped country with rich natural resources and a
populace eager for progress must have such a means of collating its own particular energies and materials if it is to
fulfill its highest potential for industrialization.
One reason for the inadequacy of transportation facilities in countries with scarce capital resources is the high
cost of constructing roads, railroads, and similar basic
components of the transport system.
If these facilities
could be constructed at lower costs per kilometer, then for
any given investment more kilometers of road or rail could
be constructed, and so a greater contribution could be made
to the economic development of the country.
1. Maximizing Value: Modes of Approach
One obvious method that could be used to extend the
mileage made available per investment dollar would be the
construction of lower quality, cheaper roads.
policy by itself is
shortsighted,
since it
However, this
can lead to in-
creased costs (gasoline consumption, vehicle deterioration,
driver salaries) for the individual user, so that ultimately
no real economy has been achieved.
Another disadvantage of
this form of construction is the maintenance expenditure required each year to keep the road in adequate condition.
If many roads in an area require a high maintenance effort
in order to keep the roadway passable, resources needed for
other projects would be unduly tied up, and so new construction would necessarily be restricted.
Since many developing
countries have comparatively little capital equipment, this
drawback can be regarded as a critical one.
On the other side of the spectrum is the alternative
of building an expensive-to-construct but easy-to-maintain
heavy duty highway system, which would have the advantage
of providing low user costs and needing very little maintenance and repair.
But this alternative also will provide
an unsatisfactory return on investment, because a government with limited capital resources will not be able to construct enough miles of road to meet the needs of the area.
How, then, can the various desirable qualities of these
two extremes be combined at an acceptable cost? The
12
research reported in this thesis indicates that in many
cases the best approach is to initiate a long-range highway
construction plan with relatively many miles of low quality
road and then to improve those roads as traffic on them increases.
This is known as staged construction.
The staged construction'of a low volume road is
the
process whereby a road is initially built to a level sufficient to meet the immediate requirements of traffic and
at a later date is reconstiuc••ed
to a higher standard in
order to decrease the costs borne by the increased traffic.
Staged construction may include changes in surface type,
changes in alignment, an increase in the number of lanes,
and other changes to the road or its environs.
The reason that the stage construction strategy is most
appropriate to developing areas is that when a road is
built
through an underdeveloped area it is at first not very heavily used.
The explanation is
quite simple.
Since there
never has been a road from point A to point B, people in A
and B have not established a social or economic reliance on
one another.
After the slow start, however, it has been
found (Haefele (48)) that as people take advantage of the
opportunities the new road provides, commerce between the
vertices--and thus traffic--increases rapidly.
Since there
will be few vehicles traveling the road in these first slow
years, the total road user costs and the maintenance expenses will be relatively low.
Later traffic increases will
permit relatively lower construction expenditures in terms
of unit costs of transport.
2. Problems of Staged Construction
Staged construction has been used in almost every road
now in existence, but this construction has not followed any
carefully analyzed long-range plan.
The costs of analyzing
staged construction alternatives are too high; too many
skilled man-hours are required to do an adequate job.
Few
engineering feasibility reports even mention the possibility
of planned staging, and when they do it is often in the context of suggesting the upgrading of a previously constructed
road.
Another reason for the lack of long-range construction
planning may be that there does not exist sufficient fiscal
stability in many developing countries to permit planning
intervals of any great length .
If this is so, then the
role of staged construction will necessarily be minimal. However, the development
-of
techniques to find low cost staging
strategies is likely to increase the interest of international lending agencies (such as A.I.D. and the World Bank) in
staged construction, and the stability provided by these
agencies should be sufficient to produce the confidence necessary for long-term planning to be undertaken.
3. Economic Issues in Staging
The goal of staged construction is to increase the
effectiveness of road investments by the closest possible
matching of the properties of the road and the needs of the
traffic at each point in the analysis horizon.
Some reasons why staged construction-can be used advantageously in highway planning are:
1. It permits a lower initial investment in a road,
thus permitting those freed (unused) funds to be utilized in other productive endeavors, either within the
transport sector or in other sectors of the economy.
For instance, the funds thus freed could be used to construct several roads in an area rather than just one.
Thus a limited amount of money could be spent over a
comparatively large mileage of low type, but adequately
designed, highways (Taylor (59)).
2.
It reduces the initial requirements for other scarce
resources such as skilled manpower and equipment, and
permits the use of these resources on other projects.
This savings of resources is due to the shorter time required to build a lower standard road and the lessened
need for specialized (i.e. expensive and imported)
equipment and labor to construct the simpler road.
3.. In cases where expected traffic increases do not
occur, an initial low standard road would entail a lower
opportunity loss than would a high standard road because of the smaller investment in the low standard
surface.
Conversely, if traffic should increase more
than was anticipated, upgrading would only require
moving up the original construction schedule, rather
than a redesign of the road.
4.
Finally, staged construction contributes to im-
proved pavement performance (in the case of asphalt and
surface-treated roads) because irregularities that develop--for example, consolidation of the subgrade--can
be incorporated as improvements in the next upgrading.
In general, this would be cheaper than performing the
type of ma3or maintenance which would normally be required if these defects appeared in an "original" surface.
But staged construction also has several disadvantages.
Among these are:
1. There may be higher road maintenance costs in the
years immediately following construction of the firststage earth or gravel road than would be experienced if
a surface-treated or asphalt surface had been built.
2.
User operating costs on the lower quality roads
would be greater.
This is due to the speedier deteri-
o.ration of these types of roads and the consequently
higher roughness values (Moavenzadeh (38)).
Because
of the high discount rates (10-15% per annum) often
used in evaluating low volume road projects, these
increased costs can have a disproportionately great
effect on the net present worth of the road.
3.
The total undiscounted construction costs of roads
which were initially constructed to the higher standard will usually be less than the costs of constructing
the road in stages because of lost economies of scale.
4. Use of Staged Construction in Project and Systems Analysis
One problem in finding an optimal construction staging
strategy is that when performing project, as opposed to
system analysis, the planner often assumes that the project
is an isolated road, forgetting that it
a larger transportation network.
is really a link in
The optimal staging strat-
egy for the road when it is considered by itself will often
be quite different from the optimal strategy for the road
when it
is viewed as one part of a whole network of inter-
connected transport systems.
Failure to take this into
account may cause the improvements to one road to lead to a
rerouting of traffic in such a way as to cause either the
under- or over-use of other,parts of the transportation
system (M4anheim (37)).
The model developed in this thesis can be used to examine the impact of changes in the demand equations on all
road-related costs; as network effects are most often expressed as changes in the demand equations, the method
presented here for investigating staged construction alternatives should prove to be an aid to highway and network
planners, even though it is primarily a tool for project
analysis.
5. Determining Optimal Staging Strategies
One of the difficulties associated with determining
the optimal staging strategy is the high cost of examining
enough alternatives to be reasonably sure that the optimal
strategy has been included in the solution space.
Unfor-
tunately, this is a situation where it is hard for rules-ofthumb such as common sense or previous experience on similar projects to approximate the answers required..
What is needed, then, is a relatively accurate, but
relatively inexpensive, means of determining the costs and
benefits that accrue to a large number of alternative
staging strategies and selecting the one which is best.
This thesis will present a computer program which will
perform this task.
The thesis presents a computer program for aiding in
the selection of optimal investment strategies for roads
in developing nations.
It discusses the factors that led
to the development of the model, the structure of the model
itself, and the interaction of the model's major components.
Finally, it presents a report of the actual use of this
model in planning for a low volume road through the
Bolivian Andes.
Chapter Two
Review of Literature
This chapter will present a review of the literature
on staged construction techniques for highways.
A variety
of approaches, methods, and decision criteria have been
formulated to evaluate staging strategies.
The strategies
range from simple pavement upgradings to those that involve
successive alignment, drainage, embankment, and surface improvements.
Decision criteria generally used in these
studies include net present worth, benefit/cost ratio, and
internal rate of return.
1. Staging Techniques
Richard Bauman's report (1) concerns itself primarily
with the forecasting of stage construction levels for
emerging countries.
He has presented two basic prescrip-
tions for the staged construction of a low volume road.
For the first method, the initial stage would have
natural grades, however steep, with sharp horizontal
curves on an earth road.
In the succeeding stages, the
gradient or vertical alignment and the degree of curvature
are progressively decreased and the road surface improved
with a higher quality surface such as gravel or some type
of asphaltic concrete.
This method has one outstanding advantage; that is,
20
it permits the construction of a low volume road at a very
low cost.
However, it has serious disadvantages.
First,
the expense of the succeeding alignment changes will be
quite high.
(This expense would, of course, be in addition
to the regular cost of pavement upgradings.)
These changes
will become prohibitively costly in rolling or mountainous
terrain.
Also, because this method leaves steep grades,
sharp curves, and rough surfaces on initial roadways, the
road user costs at this s.tage will be quite high.
could be extremely critical to development if
growth is
This
traffic
curtailed by high operating costs.
The second method of staged construction that Bauman
describes would entail initially constructing the road to
the same alignment and surface characteristics as the first
method prescribes for stage one.
For the next stage, how-
ever, the roadway alignment would be constructed to its
final alignment standards, including small gradients and
large horizontal curves, but still having a low or medium
type surface.
Successive stages then would consist of
pavement upgradings only.
The distinct advantage of this method of staging is
that only one alignment change is required.
By reducing
the number of alignment changes, there is no wasting of the
old roadway surface; the old surface can be utilized as an
improved sub-base to the newer surface.
Bauman concludes that the second method is the one
which is predominantly used in countries utilizing stage
construction techniques principally because the total costs
of this strategy, discounted over its service life, are
less than those incurred with method one.
Bauman mentions one more possible staging method.
This
method is to construct stage one to the ultimate alignment
standards but with a low type surfacing.
All subsequent
stages would be concerned with pavement and possibly drainage adjustments.
The idea here is to eliminate or at least
reduce alignment changes.
By constructing the base, sub-
base, and surface to the final grade and alignment once instead of changing them many times, sizable savings are realized.
By delaying construction of the final surface
course, savings are realized since construction and maintenance costs of the surface courses amount to 30 or 40 percent of the total costs of the road (Bauman (I)).
2. Stayed Construction: Specific Highway Techniques
This section reviews some staging techniques that
have been suggested by Robley Winfrey (19) for use in conJunction with the Interstate Highway System.
Winfrey has
investigated whether it is most economical to build the
full four lanes of a four-lane divided highway or to construct only two lanes at first, which are to be followed
some years later by the remaining two lanes.
22
Winfrey focuses his investigaticn on a specific
project (an Interstate Highway in Virginia),
using net
present worth as his measure of effectiveness.
He seeks
to determine which parts of the road should be constructed
along with the initial two lanes, and which parts should
be constructed during the subsequent expansion to a full
four-lane highway.
In the case that he is investigating,
Winfrey decides that at the time of the initial two-lane
construction all the rights-of-way which would eventually
be used for the four-lane road should be purchased,
the
roadway should be graded for the full four-lane width, and
all drainage facilities and the major structures such as
He makes this
bridges and interchanges should be built.
decision after concluding that, in this particular application, these measures would represent significant economies
of scale. The right-of-way would increase in value over a
period of time, so delay in purchase would mean increased
expenditures; the major structures, drainage facilities,
and gradings would incur large setup charges if constructed
seperately from the initial two-lane road.
Also, providing
these items at a later date would probably cause delays to
road users and create hazardous driving conditions during
construction.
What is the optimal interval between the initial construction and the subsequent upgrading?
23
Winfrey's approach
to this problem is to determine the year in which the net
present worth of all road-related costs would be greater
for the four-lane road than for the two-lane road (fig. 1),
as savings will accrue if.the remaining construction can
be delayed beyond that time.
However, factors such as con-
gestion may make it impossible to wait this long, and if
this is the case he quite sensibly recommends going ahead
and building the four-lane road immediately.
3. Staged Construction as Practiced in Developing Nations
This section will discuss some examples of the use of
staged construction of highways in developing nations.
Ex-
amples of decision rules and measures of effectiveness for
road construction in stages will be given as they have been
used in several nations.
As a specific example of staged construction in a developing country, Bauman (1) presents some standards for
staging used in Nigeria.
The data for his analysis is
from Transportation Coordination by C.B. Thompson (2).
Apparently, it is common practice in Nigeria, on a low
voltume road, to start out with an unpaved road and to improve the road surface as traffic volume increases.
For
low traffic roads, between 100 and 300 VPD, the first stage
improvement from an earth road is to a 12 foot wide bituminous surface treatment placed on a 20 foot base course.
As further increases in traffic volume occur the width of
24
20
15
10
Years to Second Construction
Costs of Staged vs. Unstaged Construction
Figure 1
25
the surface treatment is increased to the full 20 foot base
course.
Finally, when the volune of traffic reaches 2,000
VPD, the road is surfaced with hot mix asphaltic concrete.
Bauman does not indicate how these particular volumes
were determined to be the critical volumes.
Also, possible
alighmert changes were not considered as part of the staging
strategy.
Unlike Winfrey, Bauman does not explicitly dis-
cuss the element of expense in his description of his criteria for determining stage construction levels.
Another example of the stage construction technique for
highways is offered by Bonney (3) concerning a transporattion study in Sabah, Malaysia.
Bonney uses net present
worth of road costs as his criterion for determining stage
construction levels.
Bonney reduces all costs to annual costs per mile of
roadway for the sake of comparison.
He calculates this
annual cost by straight line depreciation of the fixed
facility, including interest charges of six percent.
A
feeder road was considered to have a ten-year life with
no salvage value while a trunk road was considered to have
a 20 percent salvage value at the end of its twenty-year
life.
Equations indicating the maintenance costs of earth
and gravel roads in terms of VPD were derived.
The main-
tenance equations in a/mile/year for earth and gravel roads
26
respectively are:
maintenance costs = 264 + 16 VPD
maintenance costs = 496 + 13 VPD
Bonney posits that vehicle operating costs for earth,
gravel, and bituminous roads are in the proportion 2.0:
1.2: 1.0 respectively.
The total cost per road transport
mile was calculated as 13 cents for bituminous roads.
This
works out to 26 cents per mile for earth and 15.6 cents per
mile for gravel roads.
These costs are an average for all
vehicles using the road.
According to Bonney, at 25 VPD the total annual costs
on earth and gravel roads of good alignment are:
earth: $ 940 (construction & maintenance) +
$1790 (vehicle cost) = $2730
gravel: $1585 (construction & maintenance) +
$1070 (vehicle cost) = $2655
Using this line of reasoning, since the costs are nearly
the same it becomes worthwhile to provide gravel roads when
the traffic reaches about 25 VPD.
Continuing this analysis, Bonney determines that at
80 VPD the total costs of bituminous trunk roads are approximately
equal.
He therefore suggests that it
is worth-
while to upgrade a trunk road from gravel to bituminous
surface at a traffic volume of 80 VPD.
There are several difficulties encountered in using
this type of break-even analysis.
27
The most important
drawback is Bonney's use of undiscounted costs and the
consequent disregard for the time-dependent nature of highway investments.
This in turn will often lead to non-opti-
mal investment strategies.
However, it may be argued that
this drawback is outweighed by the advantages offered by a
model so simple that it requires very little computational
effort.
The World Bank Study (4) does not present any data
concerning stage construction of earth and gravel roads,
but data is presented for varying qualities of bituminous
pavements.
For predicted volumes of 800 VPD, a low-type
bituminous pavement, for example a single surface treatment,
is recommended.
For traffic up to 2,500 VPD an intermediate
type pavement such as multiple surface treatment or a cold
mix layer is desired.
Finally, a high-type pavement like
a regular hot mix layer is recommended for volumes greater
than 2,000 VPD.
Unfortunately, the criteria and calculations
used in arriving at these decisions are not presented in
full.
A report by the Road Research Laboratory (5) indicates
that a six-inch base overlaid by a single surface treatment
is adequate for up to 150 commercial VPD.
JWhen traffic
increases above 150 commercial VPD it is recommended to add
a two-inch layer of asphaltic concrete pavement.
It is not
stated in the report how the particular staging levels were
reached.
4. Staged Construction: Pavement Design
Two frequently referenced sources for pavement
design information are the Asphalt Institute (6) and the
British Road Research Laboratory (5).
The Asphalt Institute method has been used in staged
construction of high volume highways in North America.
Bauman (1) has observed that when this method is adopted by
emerging countries, over-design results because the method
seems to be inaccurate at low volumes of traffic.
The method formulated by the British Road Research
Laboratory, however, has been used with considerable success in various parts of the world.
The method was devel-
oped for used in emerging countries and its use results,
according to the Laboratory, in a "realistic design."
5. Empirical Models
Thrower and Burt (7)
examine the possibilities of
stage construction for road pavements.
They feel that con-
crete pavements, since they have such a long initial life,
are unlikely to be considered for staged construction, and
so they have limited their discussion to flexible pavements.
Thrower and Burt consider the main problem of staged
construction to be minimizing the total costs of construc-
tion and maintenance of a pavement over a given period o-f
time; they do not mention user costs.
They present four alternatives for determining when
to begin the second stage of construction.
Case 1:
Add the second stage when the first stage has
Just reached to critical value (dc) of permanent surface deformation.*
Case 2:
Add the second stage when deformation of the
first reaches a fraction s of the normal
failure value (dc).
Case 3:
Add the second stage using criterion given in
Case 1, but assume first stage, because of excessive deterioration, plays no further structural role.
Case 4:
Add the second stage when the road is in the
same state that it is expected to be in at the
end of the analysis horizon (i.e. after the
last stage is ready for repair).
Thrower and Burt use these four cases of stage construction
to compare their costs to those of a single stage construction for the same overall life.
The sensitivity of these
costs to traffic growth rate and financial discount rate is
*The usual criterion of failure for flexible pavements in
Britain is the occurrence of 1" permanent vertical deformation in the near side wheel track, measured from the original level.
30
also investigated.
In their evaluation of the four cases, the authors
comment that Case 1 is the most optimistic assumption for
flexible construction.
Case 2, although less optimistic
than the first case, still has less total material costs
than for a single stage construction.
Case 3 is a more
pessimistic model for flexible construction.
In contrast
to the two preceding cases, total material costs are always
higher than for single stage construction.
Finally, Case 4
is often more pessimistic than any of the preceding.
It al-
ways results in an increase of total material costs.
A method has been suggested by Hewit (9) to use a
benefit-to-cost ratio, with VPD as the variable to determine at what time it is economically feasible to improve a
road surface.
The benefit/cost ratio
is defined as the
difference in road user savings divided by the difference
in highway costs, which include the cost of construction
and maintenance.
In a sample situation, Hewit attempts to determine at
what volume it is necessary to improve a road from gravel to
a bituminous surfacing.
Construction cost for the new bi-
tuminous surface road consists of the following items: preparation of the road bed, leveling course, base course, and
the bituminous surfacing.
Drainage, alignment, grades, etc.,
are considered adequate on the gravel road and therefore no
improvements are necessary.
The decision rule used in this instance is to build a
bituminous road when the benefit/cost ratio becomes one.
The equation used to determine this point in terms of VPD
of heavy vehicles such as trucks and buses is
B/0 = AR
AHl
= RG- RB
HB-H G
where AR is road user savings and AH is the cost of providing a bituminous road.
The other variables are
RG = 365 * VPD * $.34
RB = 365 * VPD * 0.28
HG = 408 * VPD * $.22
HB = $2,783 + $310 = HB1 + HB2
HB1 = Amortized cost of bituminous road over 20 years
HB2 = Annu.1 maintenance cost
Solving this equation with VPD as the variable, it was
found that the road user savings are Just equal to the annual cost of improvement less savings in maintenance cost
when the traffic reaches 116 VPD.
This means that it would
be economical to improve a gravel road to one with a bituminous surface when the truck and bus traffic exceeds 116
VPD.
The major disadvantage of this method is the use of
the benefit/cost ratio as a decision criterion.
This method
is subject to several flaws, most notably the conceptual
32
difficulty of comparing the benefit/cost ratio of a set of
projects having varying design lives (11),
and the diffi-
culty of incorporating budget constraints into one's analysis (37).
Also, this method fails to take into account
the variation of user costs with deterioration of the pavement.
6. 'Mathematical Models for Staging
The previous sections have presented a brief discussion
of the advantages and disadvantages of staged construction
for highways and have presented some examples of its use in
actual road building situations.
This section will review
the literature that has dealt with the question of how to
arrive at an optimal staging strategy.
The literature is
from fields as diverse as the selection of stocks for an
investment portfolio to the planning of a telephone system.
7. Facets of the Problem:
The Timing Issue
Construction staging has been described (Marglin (12))
as a two-part problem: selecting a timing strategy and
selecting a design.
A third, closely related, problem is,
given a set of projects and a limited budget in any one period, deciding what projects should be selected for construction in that time period (10, 11).
Some authors have assumed
that such projects are mutually independent (17) for ease in
computation, while others have acknowledged the interde33
pendency of projects in their analyses (36).
Marglin (12) offers one of the more complete discAssions of the timing problems.
He identifies the major
issue as the extent to which costs and benefits vary with
the date of construction.
He gives a decision algorithm
for selecting projects for construction if the time flows
of cost and benefits are known and there are budget constraints in every construction period.
The algorithm, how-
ever, is useful only in the case of independent projects.
Several other authors also consider the timing issue
with regard to independent projects.
Mori (10) and Gul-
brandsen (17) have developed dynamic programming computer
programs for finding optimal construction schedules for sets
of independent projects.
The approaches of Marglin, Mori, and Gulbrandsen are
quite effective with regard to computational efficiency and
project mixes.
However, they assume that each project is
the optimal feasible alternative on any given link, and
that the time stream of costs and benefits is known with
certainty.
The assumption is also made that the preferred
alternative on any link remains optimal regardless of the
status of the rest of the network.
This assumption would
imply, for instance, that an access road to a small village
would be equally effective whether or not a connecting link
was built to the market town.
This is quite obviously not
true, and this is one of the reasons that a pure timing
approach is not satisfactory in this context.
8.
The Design Issue
Manne (13) has considered in some depth a related
problem concerning the selection of an optimal plant size
and location for three industries in India given constant
annual increases in demand, substitutability of imported
goods at a known shadow price and economies of scale for
plant capacity.
Using these assumptions he finds that new
plant capacity should be added every n'th year, where for
any set of initial conditions n does not vary with time and
the additional capacity is equal to the initial plant size.
As part of this work, Manne and his co-workers developed a
computer program to determine the optimal investment strategy and plant location(s) of these three industries.
If
this concept could be used in highway planning it would be
a relatively simple matter to design and implement a computer program or other algorithm for finding staging strategies for road construction.
Manne's approach for esti-
mating the cost (both initial and operating) of a facility
was of the form C = a + b* Vk where a, b, and k are empirically determined constants and V is the annual production
capacity of the facility.
Unfortunately for road planners,
however, it appears that no similar relations exist for
estimating the costs of road construction.
35
9. Budget Constraints
Ochoa-Rosso (16) formulates the multi-period investment model as an integer programming problem. *He is concerned with investment strategies for networks and considers
the relationship between links but does not indicate how
one can optimize a single project.
Nashlund (27) expresses
the multi-period investment model as a linear programming
problem, in his case dealing with the problem of selecting
stocks for an investment portfolio under uncertainty.
Of
particular interest is his discussion of the selection of
a measure of effectiveness, which iS based upon the values
of the dual variables of the linear programming solution.
The paper by Lack et al. (37) also has some bearing on
the subject of staged construction; it
describes a computer
program which examines sixteen possible road designs.
Mod-
els for estimating construction, maintenance, and vehicle
operating costs are developed and a dynamic programming
algorithm is used to find when and what designs should be
implemented.
Limitations on expenditures have been incor-
porated through the use of LaGrangian multipliers.
model seems to be constructed quite well.
The
However, the
relatively simple cost estimating routines weigh against
its use in developing nations, especially as the cost models
are derived from Australian data and are, in the case of
maintenance and user costs, in the form of regression
equations.
Because of this it would be relatively diffi-
cult to transfer this model intact from area to area.
10.
Staging Under Uncertainty
Pecknold (36) presents an excellent analysis of staged
construction of transportation networks.
He considers both
network and project desgin, staging and the question of uncettainty in the analyst's estimates of the future.
velops the staging problem as a set of sequential
He dedecision
trees and then, using various decision rules, prunes
branches from the decision trees.
He then goes on to pro-
duce a model of the sequential decision making/ investment
staging process.
The model operates using Bayesian proba-
bility techniques to update the tree under uncertainty.
11.
Summary
The models for formulations of staged construction
which have been reviewed for the most part deal with trans-
portation networks or other large scale-systems rather than
with the design of a single link and the subsequent increase
of capacity or cost of that link.
This is particularly
true for the models of Gulbrandsen, Mori, and Ochoa-Rosso,
and true to a lesser extent for the models presented by
Lack, Manne, and Marglin, whereas the primary concern of
this thesis is the allocation of resources to a single road
project.
37
One other difficulty is that these studies (except for
Pecknold's) are deterministic in outlook.
It is felt that
due to the large demand road projects place on both the
foreign and local capital reserves of a developing country
more information should be presented to the decision maker
than is offered by deterministic analysis.
38
Chapter Three
Developing the HCM
This chapter will report on the actual process used
in developing the Highway Cost Model, the technique which
was structured to give highway planners in
developing
countries an easily used tool for determining optimal low
volume road investment strategies under conditions of uncertainty.
1.
The Basis: Cost Estimating Routines
The basis for the model grew out of previous work
aimed at developing a cost estimating routine for low volume roads.
This study, sponsored by the International Bank
for Reconstruction and Development, resulted in nine FORTRAN
programs which moeeled the processes involved in low volume
road construction, maintenance, and user operating cost (36,
38).
The construction routines are called HWYCT, EARTH, and
RFETH.
HWYCT computes 1) pavement quantities and costs,
using a geometrical approach, 2) the length in meters and
distribution of various sizes of culverts, using a model
developed by Lago (53), and 3) calls either EARTH or RFETH
to estimate earthwork volumes.
EARTH is called if a one-
point model of the terrain and final road profile is provided by the model user.
When this occurs, an estimate of
earthwork is made, assuming a zero side slope.
The quanti-
ties of cut, fill, and borrow are returned by EARTH to the
routine HWYCT.
If contour-line crossing data is supplied
rather than the one-point terrain descriptor, routine RPETH
is called.
Using relationships determined in a study for
the Department of Transportation performed by Soux (51), it
estimates earthwork quantities as a function of average and
maximum desired grades oi the road and the number of tenfoot contour lines crossed by each kilometer of the road.
It is not as accurate as the one-point model but the data
necessary to use it can often be gathered at a considerably
lower cost and without knowledge of the details of the
final alignment.
When control returns to HWYCT all costs
are summed and miscellaneous and supervisory expenses are
added to this qu atity.
See Appendix D for a further dis-
cussion of these routines.
These routines are used both in estimating the costs
of initial construction and for reconstruction of the road.
In the latter case, if the road cross section remains unaltered, the earthwork routines are not called.
The maintenance costs are estimated by a set of routines designed by John Alexander.
A complete description
of these programs is included in reference (36).
Essen-
tially, these routines estimate deterioration of the road
surface and then compute the work necessary to restore
40
some measure of the lost serviceability.
Estimates are
then made of the roughness in inches per mile, the coefficient of friction, and the rolling resistance of the
road surface.
This is done within routines MAINT and DETER.
Other aspects of road maintenance are simulated within routines SHLDR, DR4NT, and VEGT, which compute the shoulder
maintenance, ditch cleaning, and roadside clearing efforts
respectively.
MCOST sums the costs of all maintenance ac-
tivities and returns these values broken down by activity
to MAINT which then returns to NETWR' .
The road user operating costs are estimated by the subroutines USER and LOOK.
The former computes running speeds,
labor, fuel and equipment usage, costs, depreciation and
fixed charges on the vehicles on the basis of user-supplied
information and data collected explicitly for this model.
LOOK is used to interpolate within tables of data developed
by de Weille (52).
It should be noted that these models are rather extensive and although not tested in a production environment
are fairly accurate when compared with engineering feasibility studies, through comparisons made with data supplied by
the British Road Research Laboratory (57).
2. Developing the HCM
It became apparent that these routines, although they
comprised a useful tool for estimating the costs accruing
to a single road design, were not a completely successful
tool for investigating staging strategies, primarily because of the difficulties associated with communicating
with the model.
In terms of stage construction the model
was awkward to work with--i.e. it could only examine one
strategy at a time, and a great many cards were required to
define a strategy.
In evaluating a model of this nature, it was decided
that heavy consideration must be afforded to the model's
relationship with its ultimate user.
The ultimate user of
the Highway Cost Model would be highway planners in developing nations and, to a lesser extent, officials of the
U.S. Department of Transportation.
It was felt that neither
group would be very eager to use the model if it required
more than minimal knowledge of computers.
This posed two main problems: first, developing a
method for finding optimal investment strategies under uncertainty and second, developing a means of communicating
with the model user which was independent of his knowledge
of computers.
Thus, the Highway Cost Model was conceived around the
idea o-f building a "black box".
The user would be able to
throw data into it, receive his answers, and not necessarily
be concerned with the internal mechanism of the model.
addition, the technique being developed had to rely upon
42
In
the cost estimating routines developed previously.
These
routines represented a great wealth of research experience
on low volume roads.
3.
Selecting an Approach:
The Alternatives
Four methods were considered for using the cost estimating routines as a means to determine optimal investment
strategies for low volume roads.
The first method considered was to use some form of
network analysis such as GERT (Pritsker (56)).
This ap-
proach would have meant simplifying the cost estimating
routines so that they would fit into the relatively simple
structure that GERT provided, thereby losing much of the
hard-earned accuracy that had been attained.
For this
reason, the network analysis approach was rejected.
The second approach considered was to use dynamic programming (Wagner (60)) and modify the cost estimating routines so that they were compatible with the d.p. algorithm.
This approach had one major advantage--within the accuracy
permitted by the cost estimating routines, the optimal
solution would certainly be found.
However, this advantage
was counterbalanced by the very large number of iterations
that would be necessary to solve this algorithm and the consequent high computer charges associated with devoting
large quantities of computer time to a single run.
Further-
more; using a d.p. algorithm would cause the model to ex-
amine so many alternatives that only summary cost figures
could be presented unless the model user was to be inundated
with a flood of computer output.
In view of these disadvan-
tages, the dynamic programming approach was also. rejected.
The third approach invplved altering the cost estimating routines so that they would be compatible with linear
or nonlinear programming techniques.
The major advantage
of these techniques was that they automatically incorporated
resource constraints; a considerable literature existed describing the use of these techniques in capital budgeting.
The difficulty with using the linear and nonlinear programming techniques is that in order to keep the measure of
effectiveness and constraints simple, it would be necessary
to limit them to only fiscal factors.
In order to increase
the number of factors considered beyond the simplest fiscal
concerns, it -would be necessary to develop an extremely complex set of constraints and a similarly complex measure of
effectiveness.
Either alternative was unacceptable.
The fourth approach consisted of adding a set of translating and control routines to the cost estimating routines.
The function of the translating routines would be to take
a set of simple commands from the user and convert those
commands into a form that would be used to control the cost
estimating routines.
Using this approach, the planner
could draw upon his experience and knowledge to guide the
model and make up for whatever inaccuracies and biases it
contained.
The disadvantage of this approach was that a
truly optimal staging strategy would probably not be arrived at unless a very large number of strategies were
specified and examined.
But this disadvantage was reduced
in importance when it was noted that the cost estimating
routines were not accurate enough to justify the expectation that even an
exhaustive
analysis would result in a
truly optimal situation.
This last approach had several advantages.
Only minor
modifications would have to be made to the cost estimating
routines, and consequently the accuracy of the model would
not be reduced.
Also, in letting the model user retain
control of the strategies that were investigated, this
technique encourages the model user to have more confidence
in the answers which the model offers.
Finally, as the
output of the model would be a summary of the consequences
of the various strategies, and not a ranking of the strategies, it would permit the user to choose any measure of
effectiveness he desired in evaluating the various strategies.
This approach, then, permits the model user to find
a near-optimal solution by making several runs with the
model; on the first run he would normally examine a wide
variety of staging strategies, while on subsequent runs
45
he would select the most promising alternatives from previous runs, modify certain timing and design parameters,
and determine whether the new strategies are superior.
The
user could stop whenever the improvement in the measure of
effectiveness went below a certain level.
At this point he
could subject the best strategy to conventional analysis.
Thus the model user never loses control of what is happening, and he can compensate for resource constraints and/
or his own measures of effectiveness.
It was concluded
that this approach was the most nearly suited to the development of the Highway Cost Model.
The selection of this approach made necessary the
design and implementation of a set of translation and control FORTRAN routines that would interact with the previously written cost estimating routines.
Some of the factors
that influenced the design of these routines were:
effic-
iency--the routines should use as little space as possible
for storing of temporary results, yet they should also permit a reasonable number of strategies to be examined during
a single run; speed--the routines should save as many results as possible so that they would not need to be frequently calculated; minimization of input and output--in
order to reduce running time, the attempt was made to decrease the number of cards required to specify staging
strategies and increase the amount of information that was
46
always written out; and finally,, elegance--the model as
viewed by the user should be simple to operate yet
sophisticated in terms of its capabilities.
Once the translating routines were written, a control
routine was designed and implemented.
The function of this
routine is to use the list provided by the translating routine so as to cause the cost estimating routines to evaluate the staging strategies specified by the user.
These
routines, combined with the cost estimating routines developed previously, becamse the Highway Cost Model.
47
Chapter Four
The Computer Routines
This chapter discusses the computer routines of the
Highway Cost Model.
The routines are composed of two inter-
acting groups of FORTRAN subroutines.
The first group is a
set of ten routines for estimating the costs of construction,
maintenance, and vehicle operationi the second group is the
staging routines, which act as an interface between the
model user and the cost estimating routines.
These staging
routines permit the model user quickly, easily, and inexpensively to examine the costs accruing to up to thirty alternative staging strategies under an infinite variety of
traffic conditions, for an analysis horizon of up to twentyfive years.
A further function of the staging routines is
to display the consequences of the various staging strategies
in a straightforward and readily comprehensible fashion.
Since the HCM has been designed as a working tool for the
highway planner, this is an important consideration; a poor
format will discourage the planner from using the model.
For this reason a good deal of time was expended in refining and simplifying the structure of the output.
1.
The Staging Routines
There are five main subprograms in the staging routines:
they are MAIN, NETWRK, CONSTR, STRAT, and SAVDAT.
MAIN,
despite its title, is a small routine which determines the
48
level of detail presented in the output.
MAIN also calls
several subroutines: PMIN, which reads in the problem description; STRAT, which reads and interprets the staging
strategies; and NETWRK, which steps through the decision
network.
A flowchart for MAIN is given in figure 2.
STRAT is a considerably more complex routine than is
MAIN, but it performs fewer functions.
STRAT reads the
number of staging strategies to be examined during the current run, the number of road designs which are being altered,
and the number of years in which construction costs or productivities are different from those in year one.
data is read from a single card.
This
If the model user wishes
to add to or alter the "typical" templates and pavement
cross sections stored in the array DESIGN in the BLOCK DATA
subroutine, STRAT will read in the number of changed designs
and termporarily store them in the appropriate locations.
STRAT also has the ability to read in the construction
costs and productivities that are expected to be in force
over the analysis horizon.
Thus, increased costs due to in-
flation and change in productivity can be included in the
analysis and in comparing alternative investments.
By far the most important function of the STRAT routine is reading in the various investment alternatives and
interpreting this information (which is presented in a manner analagous to a decision tree) into a form which is used
49
Figure 2
Flowchart for MAIN
@B
50
A
Q)
by NETWRK and CONSTR in stepping through the decision
tree.
Briefly, this consists of 1) recognizing nodes in
the decision tree, 2) counting the branches from each node,
and 3) converting the branch data into numbers defining the
construction alternatives.
A flowchart for this routine
is given in figure 3.
NETWRK is the most important routine in this group.
It calls the cost estimating routines, performs bookkeeping,
and steps through the decision network defined by the user.
A flowchart for NETWRK is presented in figure 4.
A further function of this routine, and one that is of
considerable importance to planners, is
its capability to
examine the consequences of uncertainty in traffic projections.
This is done through a loop that encompasses the
entire routine.
When there are two or more estimates of
the traffic, the cost accruing to each is weighted by the
probability of that estimate's occurring, and used to find
the expected costs of the various construction alternatives..
The equation used to find the expected cost where
E = expected cost
n = number of traffic sets
set i
Pi = probability of realizing traffic
Ci = costs accruing to traffic set i
is:
n
=
(Pi * Ci)
52
Figure 3
Flowchart for STRAT
A
determine # of
construction
activity
i
.............
create list
of constuction activity
locate nodes
in list of
construction
activity
print list:
construction
activity,
nodes, strategies
Figure 4
Flowchart for NETWRK
determinis tic
traf. prediction
55
0
this is a network problem
C-
)57
compute foreign
exchange components of maintenance and operatin2 costs
Ft
H
locate the node
corresponding to
this construct*on
weight array
CSTRT by PNTPMF,
add this quantity
to array STCST
0
0
I
60
NETWRK steps through the decision tree by using the
list of staging strategies produced by STRAT.
Two indices
are kept by NETWRK: one for the year that is being simulated
and another for the staging strategy being examined.
Each
time the year index is incremented NETWRK checks whether
the period in question is a construction period, a node, or
the end of the analysis horizon.
CONSTR is called.
If construction is required,
If a node is located, the costs and traf-
fic at that node are saved by SAVDAT.
If
the end of an
analysis horizon has been reached, SAVDAT will print summary
costs for the investment,
examine the list
of construction
alternatives for the next strategy, and restore the costs
and traffic at that point (the beginning of the new strategy.)
SAVDAT has two functions: 1) to list and 2) to restore
the properties at a node when called by NETWRK.
The para-
meters passed to this routine define the node, and establish whether a save or restore operation is to be performed.
The information saved is a complete description of the road
at the time SAVDAT is called.
This includes costs to date
(discounted and undiscounted), the road template and cross
section, traffic levels and operating costs per kilometer,
and the material and currency consumption required by the
previous construction activity.
A flowchart for the SAVDAT
routine is given in figure 5.
CONSTR performs the same type of bookkeeping and
Figure 5
Flowchart for SAVDAT
TYPE is set
by NETWRK
62
control functions as are done by NETWRK.
Specifically,
CONSTR takes from the BLOCK DATA subroutine details of the
road template and cross section, selects the costs appropropriate to the year in which construction occurs, and
then calls HWYCT to compute the costs of construction.
When control returns to CONSTR, costs, material quantities,
and earthwork volumes are summed and printed.
Surface con-
ditions such as roughness and frictional coefficients are
initialized by a call to INITL.
Subsequently, the foreign
exchange components of construction costs are computed on
the basis of material, labor, and equipment expenditures.
CONSTR can, if desired, cause PMIN to read in a new
set of vertical points of intersection (VPI's) and topographical data.
This information is written over the cur-
rent data sets and used in further analyses.
This permits
the user to examine the consequences of constructing roads
on different alignments.
A flowchart for this routine is given in figure 6.
2.
Relationship to Cost Estimating Routines
Although the previous section has given a brief indi-
cation of how the network routines are related to the cost
estimating routines, this section describes in a more explicit form both the calling sequences and the information
passed between the two sets of subroutines.
Figure 7 shows the calling sequences used in the HCM.
63
Figure 6
Flowchart for CONSTR
write
identification
construction
JQ is the
design number
A
0
TOP is the type
of~construction
initialize
array RCOND
0)65
B
Figure 7
Calling Sequences
line indicates
hat does not
·ily occur.
To read it, start at MAIN.
The order in which the routines
are called is given by the clockwise arrow.
Thus, routine
MAIN calls PMIN which may call FORIN (if foreign exchange
requirements are to be read).
MAIN will then call STRAT
and NETWRK, which in turn will call CONSTR (or SIMCON if
a single investment strategy is being examined).
When con-
trol is returned to NETWRK it calls USER and MAINT to find
the costs of vehicle operation and road maintenance.
The
year index is then incremented by one, and a check is made
to see if a node or construction perid has been reached.
If this has occurred, NETWRK takes the appropriate action--
calling CONSTR to simulate road construction, or, in the
case of the node's being reached, calling SAVDAT to save
the conditions at the node.
3.
The Highway Cost Model Flowchart
Figure 8 presents a macro flowchart for the entire
Highway Cost Model.
It shows the flow of control in terms
of issues, decisions, and operations in a format which is
not directly related to the formal (i.e. FORTRAN language
subroutines) structure of the HCM.
As can be seen in this
figure, the major issues considered here are the tradeoffs
between different maintenance, construction, and vehicle
operating costs, the effects of uncertainty in traffic projections, and the need to communicate with.the model user.
It is hoped that the simplicity of the input and the
68
Figure 8
Macro Flowchart
69
A
a
constructhis
yes/
tion
1periodsl
get road design
and unit costs
from storage
no
get maintenance
policy from
storage
Ir
compute costs
and resources
consumed in
construction
--
initiali7ze
surface
conditions
-4
"
[
compute road
user costs
and traffic
make traffic projections on basis
of demand curve,
growth rate, and
per kilometer costs
B
70
C
B
compute deterioration of road
and right of way
I
compute necessary
maintenance effort
on basis of maintenance policy
and deterioration
year = year + 1
store costs
and traffic
at this node
yes
•
tia is
this a
node
no
G
D
72
clarity of the output will make this model and the information it provides accessable to even the relatively inexperienced computer user.
73
Chapter Five
Experiments in Staged Construction:
Techniques and Results
Several experiments were performed using the Highway
Cost Model to test the hypothesis presented in Chapter One,
namely that staged construction of low volume roads would
reduce the discounted cc• . s•.
-
construction, maintenance,
and vehicle operation under a variety of circumstances.
This chapter will discuss the experiments that were performed.and present the results of these experiments.
The
experiments which were run served to develop a set of
pruning rules that the model user could draw upon.
These
pruning rules, which embody the conclusions drawn from these
experiments, make the planner's work easier as he can use
these rules to decrease the number of designs and staging
strategies which he must examine during the first iteration.
Chapter Six will discuss the implications of these experiments for planners of low volume roads in general and users
of the Highway Cost Model in particular..
1.
The Experiments
One of the great advantages of using a computer simu-
lation of a real-world situation is the ease with which experiments can be performed and hypotheses tested.
The HCM
is an excellent example of this statement; it can inexpen-
sively and accurately investigate.the effects of various paramters, decisions, and other factors on the costs associated
with low volume roads.
Previous work with the cost estimating routines (38)
indicated that the most significant parameters affecting
low volume road costs were traffic conditions and terrain.
Considerations of lesser importance were the discount rate,
the length of the analysis horizon, and factor prices and
other site-dependent conditions such as the productivity of
the construction work force and the vehicle mix.
In order to learn as much as possible about the effectiveness of various construction staging strategies, the
following procedures were used.
First, a set of feasible
construction strategies were defined for a situation in
which 1) reconstruction could occur only at five-year intervals and 2) the roads to be considered were earth and gravel
one- and two-lane roads and surface treated and asphalt
paved two-lane roads.
This set of twenty-five strategies
represented a fairly full range of choices available to the
planners of the stage construction under these conditions.
Figure 9 shows these staging strategies, presented here in
the form of a tree where every path from year zero to twenty is a distinct staging strategy, with reconstruction or
upgradings of a road occurring at the nodes of the tree.
(For the experiments that were run, the one-lane roads were
EARTH2S
GRAVEL2
SURFACE
ASPHALT
GRA.VEL2S
SURFACE
ASPHALT
SURFACE
ASPHALT
LW.J.J
44"
SURFACES
S
ASPHALT
ASPHALT
ASPHALT
ASPHALT
ASPHRNW
ASPHRNW
ASPHRNW
15
YEAR: 1
The Staging Strategies
Figure 9
76
removed from consideration as at all but extremely low levels
of traffic they resulted in excessive unit costs of vehicle
operation.
Therefore, under the generally higher traffic
levels normally used in the experiments, examining these
alternatives would have been a waste of time.)
A five year-interval between reconstruction periods
was chosen because 1) the total discounted costs of construction,maintenance, and vehicle operation did not vary
more than a few percentage points when reconstruction was
delayed or speeded up two or three years, and 2) five-year
intervals were well suited to the format used for input
of construction strategies to the HOCM.
It should be noted
that this interval is not limited to multiples of five
years; the HOCM can consider intervals of any integral
number of years.
2.
The Scenarios
In order to examine the effectiveness of the various
staging strategies they were tested under a wide range
of conditions.
The procedure used was to take two "base"
scenarios and vary the design and cost parameters.
The
base scenarios were taken from two engineering feasibility
studies.
The first, performed by Louis Berger, Inc.,
investigated National Route 14 in Argentina.
done by Baker-Wibberly
The second,
, reported on the Sapecho-Puerto
Salinas road in Bolivia.( 62,63 ).
77
The two roads differed in many respects, including
traffic volume, terrain, and suggested design.
The Arg-
entine road was asphaltic concrete, designed to carry
fairly high levels of traffic on a straight, flat embankment on a floodplain north of Buenos Aires.
The Sapecho-
Puerto Salinas Road, on the other hand, was expected to
carry relatively little
traffic through the Andes,
fifty
Appendix C contains the
miles northeast of La Paz.
data
which was used to represent the base scenarios of both
roads.
Even though these roads seemed to encompass the
extremes that would be encountered by planners, it was
felt that
firmer conclusions could be drawn and pruning
rules formulated if the staging alternatives had been
examined under a wider variety of conditions.
3.
Expanding the Parameters
To obtain an expanded number of parameters for this
experiment, the following manipulations were made to the
base scenarios:
the traffic volume was varied, the terrain
data was switched (that is, taking the terrain data from
the Bolivian site and combining it with the cost factors,
designs, and traffic volume and types of the Argentine
site, and vice versa), and several discount rates and analysis horizons were used.
Specifically, the three parameters
which define expected traffic--initial level, elasticity
7t
of demand, and annual growth rate--were varied from the
values given by the engineering feasibility studies; then
the costs of each staging strategy was determined.
Tables
1 and 2 show the traffic, growth rates, and price elasticities used for the Argentine and Bolivian roads.
4. Elasticity of Demand
To test the effects of increasing elasticity of demand,
a series of experiments were performed with input data
identical to the base run in all respects but one--the
elasticity of demand for all vehicles was increased to five
percent.
The total discounted costs of the twenty-five
strategies for both the high and normal elasticities of
demand is given in figure 10.
As this figure shows,
increasing the elasticity of demand caused significant
reductions in total costs for the better strategies even
though in some cases it increased the costs of the lower
quality strategies.
The changes in costs were almost
completely limited to operating costs;
the elasticity of
demand is a factor in determining the traffic volume of
the road so only slight change in maintenance occurred.
In general, increased elasticity tended to make improved
roads better choices, since the increased elasticity of
demand generated more traffic and increased the consumer
surplus on the higher quality roads.
However, the increased
traffic caused increases in the total costs of vehicle
79
Vehicles/Day
Base Cost$/KM
15.
1.342
15.
2.405
5.370
30.
75.
75.
150.
150.
150.
300.
Elasticity
0.012
0.003
0.003
0.090
0.090
0.090
0.012
0.003
0.003
0.090
0o.o090
0.090
1.342
2.405
5.370
0.012
0.003
0.090
0.090
0.090
1.342
2.405
5.370
0.012
0.003
0.090
0.090
0.090
0 .ogo
1.342
2.405
5.370
0.003
Other Growth Rates
.18
.18
.18
Growth Rate
Other Elasticities
.045
.045
.045
0.050 and 0.0
Traffic Conditions for Bolivia Data
Table 1
6O
Vehicles/Day
Base Cost$/KM
Elasticity
Growth Rate
35
0.255
0.012
0.066
15I.
o0.357
2.200
2.265
0.003
0.042
0.042
16·.
9 ;.
5 i..
170 .
75
80.•
43 .
22 .
0.003
0.003
0.009
2.366
0.042
0.037
0.066
0.012
0.003
0.003
0.255
0.357
.2.265
2.366
0.003
0.009
0.042
0.042
0.042
0.037
345 i.
0.255
148 .
157 •
0.357
0.012
0.003
0.066
0.042
0.042
44
2.366
0.003
0.003
0.009
'2.200
2.200
2.265
86
Other Growth Rates
.122
.084
.084
.084
.074
0.042
0.037
Other Elasticities
0.050
.033
.021
.021
.021
.018
and 0.0
Traffic Conditions for Argentina Data
Table 2
56.
Q.
i.
O
54.
.9
*O0
4.4-
0
0
+
52
0
O
fl,
C
o
0
0
50
o
oC
-,
+1
O
0
0
O
48
0
0 46
44
o Elastic Traffic
+ Normal Traffic
0co
1'5
Strategy
Argentina:
Costs due to Normal
and Highly Elastic Traffic
Figure 10
82
W
m
operation and thus caused the incogruous situation of
gravel roads having lower total user costs that surface
treated roads over the analysis horizon.
(It.should be
noted that this situation arose only in cases of very
elastic demand.
Fortunately for planners, it
seems that
traffic in developing nations is only slightly elastic
andl so this situation is not likely to occur (Soberman (55),
Haefele (48) )).
5. Growth Rate
Next, the annual traffic growth rate of the base
scenarios was varied.
In the HOM the user generally spec-
ifies this parameter as an annual percentage increase; the
traffic in year n + I is given by the expression
1
Tn+1=
[tin
* (1. + gi/100.l
where tin is the traffic in class i in year n and gi is
the growth rate of traffic in class i.
Due to the multiplicative nature of this parameter,
small changes in it lead to considerable variations in
traffic over the life of the road.
For this reason, and
also because of the difficulty in estimating the growth
rate of traffic, three growth rates--low, medium and high-wer associated with each class of vehicle, and the effects
were noted.
The experiments showed that high growth rates were
associated with reduced costs for high type roads, and
low growth rates favored poorer quality surfaces (Figure 11).
This was even more apparent when the discount rate was
increased from its normal value of seven or eight percent
to ten or twelve percent. Figure 11 shows the costs
of the Argentine base scenario for growth rates of seven
and, twelve percent.
6, Maintenance Policies
The Highway Cost Model permits the model user to specify a wide range of both labor and capital intensive
maintenance policies (Table 3).
Six such policies--poor,
normal, -and excellent capital and labor intensive maintenamce--were defined, and their effects on the utility
of the various staging strategies were noted over several
sets of initial traffic conditions.
The tradeoff that occurs is that increases in
maintenance reduce the unit cost of vehicle operation,
while reductions in maintenance increase the unit cost
of vehicle operation and may lead to the need for more
frequent reconstruction of badly deteriorated surfaces.
Because a relatively small percentage of total costs are
due to maintenance activities, earth and gravel roads in
both flat and rolling terrain had lower total costs when
excellent maintenance policies were used than they had
when poorer maintenance was given.
64
The reduced total costs
+ Low Growth Rate
54
.
0
* High Growth Rate
.
.
a
oo
+
.
Oc0
0' E
4.
+
+
0t
4
.9.
÷
0
s
1,
ý).
CD
W+P
t
(10000's)
46
_1
5
Strategy
Increasing Strategy Quality
I
Maintenance
Policy
_
Poor Capital
Intensive
Blading
Frequency
___
Rut
Fraction
Filled
Maximum
Rut
Depth cm.
1
__ __
10,000
2.0
Normal Capital
Intensive
5,000
1.5
Excellent Capital
Intensive
2,500
1.0
Poor Labor Intensive* 10,000
2.0
Normal Labor
Intensive
5,000
1.5
Excellent Labor
Intensive
2,500
1.0
* Labor intensive maintenance is not as effective as
Capital Intensive Maintenance for Gravel and Earth
Road Blading
Capital and Labor Intensive
Maintenance Policies
Table 3
86
were due to the higher velocities made possible by the
increased smoothness of the
highly maintained roads, and
the consequent reduction in time dependent expenditures.
This is shown by figure 12 which gives total vehicle
operating costs over the analysis horizon for earth and
gravel roads
on the Argentine alignment for poor, normal
and, excellent capital intensive maintenance.
Figure 13
shows the velocity of each vehicle class on route 14
in year five for poor, normal and excellent capital
intensive maintenance.
The situation is slightly different for surfacetreated and asphalt roads.
On both these surfaces, rela-
tively little maintenance is required in the first years
after construction, but in suceeding years more maintenance
is required each year until reconstruction.(Figure 14).
Also, due to the way in which these roads are maintained,
labor and capital intensive maintenance techniques are
essentially identical, differing only in such tangential
aspects as ditch cleaning and vegetation control (Vance (61)
Alexander (36)).
For this reason both surface treated and asphalt
roads exhibit similar maintenance and vehicle operating
costs over the:.first seven to ten years of the analysis
horizon, after which costs increase more rapidly on the
surface treated roads.
Therefore, an often economical
1.2
1.0
0.8
0
o
0.4
U)
0I
0.6
0.2
U.U
U_
poor
I
I
normal excellent
poor
Earth
normal excellent
Gravel
Per kilometer operating costs vs.
Maintenance Policy
Figure 12
50
45
0
4J
'40
035
O
+
30
*
Vehicle 1
0 vehicle 2
+
vehicle 3
I
SI
poor
normal
Ir
!p
I
excellent poor normal
excellent
Gravel
Earth
Maintenance Policy vs. Velocity
Figure 13
* Asphalt
+ Surface Treated
Reconstruction in year 18
5.
6·
35
1 .
2O
Strategy
Maintenance Cost of Asphalt and
Surface Treated Roads
Figure 14
90
staging policy is to build a surface treated road and,
when the serviceability index reaches the range 1.5 to 2.0,
(Alexander (36)) to build the final layer of asphalt.
Experiments made with the HCM have shown that this procedure
often reduces total discounted costs over a wide range of
initial traffic conditions and a range of discount rates
from seven to twelve percent . per year (Figure
7.
15).
Discount Rates
In recent years, interest rates on development loans
have been increasing rapidly; where rates of two or three
percent were once common, some projects in recent years
have been evaluated at discount rates as high as fifteen
percent.
In part, these increased rates reflect the demand
for risk capital; they are also partly due to the high
rate of inflation occurring in many parts of the world.
Several experiments were run using the HOM to test the
desirability
of the various strategies in view of this
important factor.
The experiments showed that higher
discount rates made the use of staged construction even
more advantageous, because the compunding of the discount
rate
causes future expenditures to wigh less heavily than
present expenditures.
Figure 16 shows the total discounted
costs accruing to the twenty-five strategies on the
Argentine route for interest rates of seven and twelve
percent.
Asterisks (*) indicate those strategies where
150.
*
130 .
110.
90.
C
oo
3
0
,
70.
O
4-
c 50.
V)
.r4
r-4
o Asphalt road, no reconstruction
E-r
* Surface treated road, reconstruction at PSI = 1.5
T
r
Traffic
low
normal
high
low
Interest= 7%
•
normal
Interest= 12%
Advantages of Staged Construction
Figure 15
high
160
140
Interest Rate = 7%
e
S
0
a 120
0
o
o
o
Cý
-100
0
e
*
0
&
o
80
860
0
40
*
*
6
9*
0
5
1
0
60
#
*
A
*
**
d
0
Interest Rate=12%
0
A
A
40
16
15
*
20
Strategy (Increasing Road Quality)
Effect of interest Rates on
Total Discounted Costs
Figure 16
93
*
A
25
staged construction did not occur.
8.
Foreign Exchange
Foreign exchange consumption can often be an important
factor in deciding what type of road to build.
The limited
foreign exchange resources of most developing countries
make necessary the careful consideration of the uses to
which this resource is put.
Some roads will require more
foreign capital than others, either because they are more
expensive or because their design requires greater quantities of imported materials or equipment to build.
Foreign exchange requirements are calculated in the
HCM by asking the user to state the percentage of vehicle,
fuel, tire, construction and maintenance equipment,
construction labor, and construction material costs that
must be purchased using foreign exchange.
the percentages used for both data sets.
Table 4 shows
These percentages
were used to estimate foregin exchange consumption by use
of expressions of the form
Foreign exchange
7
F= I•
needed
(unit costi a consumption i
1=1
* percent offshore costs)
. exchange rate]
where the subscripts refer to the seven categories described
in Table 4.
The way in which offshore costs varied with staging
Percent Offshore Cost
Item
Vehicle
80.
Labor
43.
0.
Construction Material
Fuel
70.
Tires
80.
Construction Equipment
100.
Maintenance Equipment
100.
Foreign Exchange Component
of Costs
Table 4
95
strategies for medium levels of traffic in Argentina is
closely related to the way in which total costs varied,
with the single exception that earth roads were considerably less expensive in terms of foreign exchange than the
total costs would indicate.
Examination of the offshore
costs accruing to different levels of traffic showed similar effects.
Figures 17, 18, and 19 show foreign exchange
costs for the twenty-five strategies for the three traffic
levels previously described.
By reference to figure 9 one
can see that strategies 1 through 10 were initially earth
roads, 11 through 17 were initially gravel and the remainder
Thus, in those cases where
were surface treated or asphalt.
foreign exchange consumption is an important consideration,
high type roads may be preferred to poorer quality surfaces
even though higher initial construction costs will be incurred.
g. Length of the Analysis Horizon
Because any fixed-length analysis period represents a
length of time which is shorter than the total life of the
road involved, any analysis of the road which considers only
that period will be somewhat misleading.
For example, if
two or more staging strategies are compared, the length of
the analysis period will affect the ranking of the alternatives.
Consider the impacts of the following strategies
in the case of Argentine Route 14.
96
Strategy 1 consists of
140
.130
120
110
100
1
-
1
·
Strategy
i5
-
Foreign Exchange Requirements
Argentine Route 14 Low Traffic
Figure 17
97
--
20
25
0
0
190 -
.180 -
O
I0
0
o
,
170
UO
160
O
150
140 -
1AO
5
10
15
20
Strategy
Foreign Exchange Requirements
Argentine Route 14 Normal Traffic
Figure 18
25
320
4
O
a
44
O
0
g
ra
O
0
B
0r
(r'
O
230
Br
I
0r
200
1 70
5
15
10
Strategy
Foreign Exchange Requirements
Argentina Route 14 High Traffic
Figure 19
99
20
25
building an asphalt road and giving it normal maintenance.
Strategy 2 consists of initially building a surface treated
road and upgrading it to asphalt in year fifteen, giving it
normal maintenance throughout the analysis horizon.
Given
an analysis period of twenty years, it is unlikely that
Strategy 1 will have lower discounted total costs.
But if
the analysis period is lengthened to twenty-five years, the
situation may be reversed--the asphalt road will have required reconstruction and in the interim the user costs will
have increased to more than compensate for the costs of upgrading the surface treated road.
The costs over time of
both roads would be given as in Figure 20.
This implies
that longer analysis periods favor roads that are reconstructed
in the last half of the analysis period, while
shorter analysis pFriods are more favorable to construction
strategies having only a single construction activity.
10. Results of the Experiments: The Pruning Rules
The experiments Just described examined the costs
accruing to twenty-five different construction strategies
under a very large number of conditions.
As has been
noted, one of the ob3ectives of running these experiments
was to develop a set of pruning rules which planners could
use to reduce the time and effort required to arrive at an
optimal investment strategy whether or not they used the
Highway Cost Model.
100
5
0
oo
0
o
4vo
0
0
u
No Staging
Staged Construction-
4-,i
0
-HO
H(
_
1
__
10
Year
15
Bolivia:Costs to Date of Roads both
.Using and not Using Staging
Figure 20
101
25
The remainder of this chapter will discuss a set of
pruning rules which have been developed using as a measure
of effectiveness the total discounted costs of each staging
strategy.
11i.
Rules for Flat Terrain
For all but the lowest i.e., less than twenty-five
vehicles per day over the analysis horizon, levels of
traffic, growth rates, and price elasticities of demand,
the lowest net present costs occur when a surface treated
road is initially chosen.
As traffic warrants, it may be
desirable to upgrade to an asphalt road at year ten or
fifteen (assuming a twenty year analysis horizon)..
Discount rates greater than ten percent favor resurfacing
and minimum construction expenditures in any one year.
Heavy vehicle loadings' (in terms of the number of
vehicles using the road and their weight) increase the
desirability of an asphalt road, except at exceptionally
high (greater than ten percent) discount rates.
In most
cases, surface treatments and resealing would s'eem to
be adequate.
12..
Mo.untainous Terrain
For low and medium levels of traffic, gravel roads
appear to be best in terms of total discounted costs.
Earth roads are acceptable in mountainous regions if traffic
102
is initially very low (under twenty-five vehicles per day)
and increasing slowly, on the condition that good or excellent maintenance can be obtained.
As velocity on mountainous roads is limited by the
grade, asphalt or surface treated roads generally result
in only small savings for road users.
Unless the expected
traffic is exceptionally heavy, the savings will be less
than the cost of the. asphalt layer.
High traffic growth rates suggest a need for better
roads, but the opportunity loss due-to unrealized traffic
growth and a more expensive surface may well be greater
than the additional user costs due to running on a gravel
surface.
Unless high traffic levels are
very probable,
a gravel road would be preferred.
Longe3 flatter routing of mountain roads (that is,
going around the mountain rather than going over the
mountain) may reduce both construction and vehicle operating
costs if the following expression is true
# km * uc/km
>(#
km + akm) * (uc/km -
Auc/km)
where
# km is
the original leng.th of the road
a km is the additional mileage constructed on the
flatter routing
uc/km is the per vehicle operating cost on the
original routing and
103
6uc/km is the reduction in per kilometer operating
costs as a result of flatter grades
If
it is, the increased costs due to extra mileage will
be less than the savings caused by less earthwork and
lower. grades.
Of course, this is very dependent on the
original and alternate alignments, but as the HCM permits
the use of contour line crossing data this alternative
could--and should--be inexpensively explored.
13.
Maintenance
The experiments performed during this research
suggested that capital intensive maintenance is least
costly for many earth and gravel roads.
However, as this
course of action can lead to foreign exchange consumption,
it may be desirable to use labor intensive maintenance at
the expense of an increase in total costs.
For the
factor prices and productivities used in these experiments,
it
costs more do to a given amount of work using labor
intensive techniques than to do the same work using capital
intensive procedures.
However,
different factor prices
and a high shadow price for foreign exchange may make
labor intensive techniques preferred.
The interesting
tradeoff here is the ease of establishing a labor intensive
work force against the increased cost of maintenance.
One
must recognize that, in an economy having high levels of
104
unemployment, the shadow price of labor is less than the
wages paid.
For example, by employing unemployed workers,
one may be eliminating
relief funds.
the expense of providing them with
For this reason, the creation of a labor
intensive maintenance force may be less costly than is
indicated by the HCM.
14.
Pruning Rules: Other Issues
Staged construction can be counter-productive unless
the commitment to staging is kept.
A road built with
the expectation of being upgraded in ten years can be a
definite hindrance to development after that date if it
is
not improved.
Maintenance is a far more important issue than it
is usually considered to be.
Poor maintenance procedures
and policies should not be used for more than five years
at the very most, or most of the original investment may
be lost due to the encroachment of vegetation, loss of
surface materials due to traffic, erosion, and other
factors.
For this reason, effective maintenance agencies
should be formed during the construction of the road, and
not left until maintenance is badly needed.
Finally, unless there are very strong reasons for
only using one analysis horizon, the planner should
examine the alternative staging strategies for their
effectiveness at periods five years longer and shorter
105
than the length of the nominal analysis horizon.
15,
The Use of the Pruning Rules
What can the planner do with these pruning rules and
why are they important to him?
isthat
The answer to these questions
the pruning rules will make it
easier for the plan-
ner to determine an optimal investment strategy.
This is
because he can use these rules to discard a large number of
undesirable strategies at the beginning of his investigation
--for example, earth roads and all staging strategies deriving
from earth roads--and replace them in his input to the HCM
during the first iteration with a wider range of gravel and
surface-treated designs, staging strategies, and maintenance
policies.
Essentially, the use of the pruning rules enables
him to combine the work of the first and second iterations,
thereby reducing by as much as a third the time and effort
required to obtain an optimal strategy.
106
Chapter Six
Use of the HCM
This chapter describes the use of the HCM in an experimental situation, namely, searching for an optimal design
for the road between Sapecho and Puerto Salinas in Bolivia
(see figure 21.).
The entire scope of activities associated
with using the model--from data collection to design and
engineering decisions--will be considered.
Topics covered
are data collection, i.e. what type of information is required, possible sources, and the required accuracy of this
information, and the development of staging alternatives
through the use of pruning rules and engineering judgment.
Also discussed is the iterative search of the decision space
with regard to the timing of investment and road design;
maintenance policies ranging from poor labor intensive to
excellent capital intensive maintenande; and the issue of
uncertainty in traffic projections.
1.
Data Collection
The matter of data collection is perhaps the single
most important area of interest in this section, as whatever results are obtained by the model are only as precise
and useful as the data which has been used as input.
The area where the most attention to accuracy should
be given is the construction cost and the productivity
107
'I
!
Map of Sapecho-Puerto Salinas Route
Figure 21
108
data.
This is because 1) on most low volume roads, con-
struction costs are the major component of total road transportation costs, and 2) in the productivity data, errors
frequently have the same bias--for example, consistently
underestimating productivity--to a greater extent and significance than occurs with costs related to maintenance and
user operating costs.
The reason for this bias is
that the
required data will often come from one or two closely related
sources and any error made in either source will thus be
propagated.
(In the remaining areas of data collection,
however, there will almost always be a wide variety of
sources, so that the possibility of offsetting errors is
increased.)
2. Construction-Related Data
There are three groups of construction-related data
that are required by the HCM.
They are: 1) site-dependent
factors such as alignment, haul distances, and topographical information; 2) materials, labor, and equipment prices,
which can often be considered fairly constant over a large
area; and 3) design variables such as pavement cross sections, templates, and maximum and average grades.
In the first stages of the design process, I feel that
the greatest effort should be expended in determining the
values of the second data set, as both the.first and third
groups are much more easily manipulated by the model user.
109
It is a simple matter, for instance, to change a road cross
section, but it is quite difficult to alter the productivity of labor or the unit costs of pavement construction.
The prime source for construction-related data would
be engineering feasiblity studies of roads in the same area,
progress reports from construction projects in that region
showing cost and resources consumed in performing a given
amount of work, and summary figures for previous construction activity.
Of course, the planner should be careful to
establish that the figures used are not taken from a different type of construction organization from that which is
expected to construct the road under question.
For example,
domestic and foreign constructors often operate at significantly different levels of performance and cost.
Thus
using the wrong data set would probably cause errors of considerable magnitude.
The other construction-related data, especially the
site-dependent factors such as alignment, horizontal
curvature, haul distances, and terrain desriptions, can be
roughly estimated at the early stages of work and given -in
greater detail as more data becomes available. For instance,
terrain properties can first be described by using contour
line crossing densities and later be replaced by a one-point
descriptor of the roadway center-line when details of the
alignment are better known.
The'tradeoff between costs of
110
data collection and accuracy of the answer cannot be explicitly stated; however, it is suggested that the best available maps be used during the design stages and that if the
model is used during the final design stages, less than
total reliance should be placed on earthwork volumes and
costs since the one-point model, although inexpensive to
use, is inaccurate when used on terrain having a non-zero
side slope.
Design variables can be specified in either of two ways:
first, by letting the model specify the designs, or second,
by explicitly specifying designs to replace those stored
in the model.
Unless there are extraordinary design re-
quirements, i.e. very thick or thin pavement layers or narrow or wide lanes, it is often most convenient to let the
model specify the designs for short cut analysis.
3. Maintenance-Related Data
This class of data is often the easiest to collect,
due to the small number of items that comprise it--maintenance policy, equipment rental rates, and material costs.
The policy data can be supplied by the model or the user,
and the per hour costs of equipment and men and the unit
prices for materials can frequently be determined by reference to readily available sources within the maintenance
division.
In any case, since maintenance costs are usually
only a small percentage of total costs, the total cost is
111
fairly insensitive to errors in these figures.
Also, since
costs are computed on the basis of resource consumption,
errors in estimating the cost of maintenance will not affect
the way in which the maintenance is performed.
Thus it can
be seen that the user should not devote extensive resources
in determining these numbers during the preliminary design
stages.
4.
Data Related to User Operating Costs
User operating -cost is a fairly sensitive area, as
indicated by the research presented in the DOT report (57).
The points .of greatest concern are the initial.costs of
the vehicles and the per hour costs for the vehicle and
its driver.
Data derived from run #150, which was the base
run for this analysis, showed that on a gravel road with a
roughness of 512 inches per mile for commercial vehicles
driver costs were between 11 and 23 percent of total market
costs while vehicle expenses due to the initial cost of the
equipment and tires was between 44 and 62 percent of total
market costs.
It must be recognized that these percentages
vary with the road characteristics and, perhaps more importantly, with the user's definition of costs.
The cost fig-
ures that were used as input to the HOM were admittedly uncertain and it is unlikely that these would be the exact
figures derived if completely accurate data was used.
112
How-
ever, the use of other, more accurate, data (derived from
the Argentine National Route 14 study) yielded similar results.
Sources of information on user operating costs are
likely to be readily available, but confusion may arise as
to the distinction between market and economic costs as
they are used by the model.
"Market cost" refers to costs
that are borne directly by the user, such as taxes, import
duties, registration fees, purchase price, and similar items
which will be paid for out of the user's pocket, while
"economic cost" refers only to the cost to the economy, i.e.
the price of the resources lost to the economy by the purchase and use of the vehicle and/or its accessories.
The most important user operating costs are the initial
prices of the vehicles and the gross weights of the vehicles
(since these have significant effects on the deterioration
of the road surface.)
Figure 22 is a reproduction of the input data as
echoed and annotated by the Highway Cost Model.
By examining
this illustration one may learn: the characteristics of the
road alignment; the costs and productivities of construc.tion; the-normal maintenance policy; the topography along
the road centerline; the California Bearing Ratio (CBR) of
the subsoil; the percentage of the roadway that has heavy,
normal, and light groundcover; some of the hydrological
113
C
PAINTENANCE
0
USER
0
OUTPUT SWITCHES FOR THIS RUN ARE CCNSTRUCTION
OUTPUT IS PRINTED FOR YEARS THAT ARE A MULTIPLE CF 20 UNLESS THIS NU912ER 1 IS POSITIVE
INITIAL TRAFFIC CONhITIONS ASSOCIATED WIT7
3 SETS OF
THE TRAFFIC GROWTH SWITCH IS -1 AND THERE ARE
.
THIS PRCJECT
CATE 0/ 0/ 0
RUN 170
BOLIVIA TEST OF 25 YEAR ANALYSIS
ALIGhNMENT DATA-ALIGN
LENGTH
UEG-CLRVE
6.10
15.00
PROfILIDATA- PPCF
TYPE-SWITCH AVE-GRADE PAX-GRAOE NO-VPIS
9.29
15.00
-1.00
6.72
VPI STA
VPI ELEX VPI STA
VPI ELEV
VPI STA
VPI ELEV VPI STA
VPI ELEV VPI STA
V PI ELEV
7q0.00
1)13.00
835.C0
2100.00
0.0
896.00
140.00
886.00
600.00
9CC.U0
722.00
3660.00
702.00
3Q)0.010)
714.CC
4100.00
700.00
720.00
3140.00
d900.Oo
00.00
67C.00
4270.00
712.C00 460.00
680.00
4900.00
672.0C
55920.3
619.00
KUAAOuAD
••uSS SECTIONIHCRIZONTALI-TEPPL
FILL-SL
PAVE-hC
WIDTH
SLOPE
SHLD-W0
SHLD-SL
DTH-WO
CTH-SL
'u4-wO
0TH-SL
CUT-SL
1.50
4.50
2.00
1.CC
0.75
0.03
0.82
0.25
1.00
ROADWAY UctIGN DATA(VERTICAL)-PAVE
THICK2
THICK
SHLD-TPE
THICKt
THICK
AOT-TPE
MAT-TPE
THICKNESS MAT-TPE
PAVE-CD
LAYERS
0.C
2.00
3.00
4.00
0.18
0.0
0.0
0.o
O.C
2.00
0.18
ECONUMIC DATA
•u OF PcrlOUS.DISC. RATE, NO OF VEHICLE TYPES
6.00
?
20
FUrEIGN RATE CF EXCHANGE
I PESU
x
0.09330 DCLLARS
PERCENTAtE OF COSTS THAT CRIGINATE FRCM FOREIGN SOURCES
Pkl CENT OF VEFICLE COST * 80.00
PER CENT CF FUEL COST - 7T.0CFER CENT CF TIRE COST * 8C.0C
PER CENT CF CONSTRUCTION EQUIPPENT COST
10CO.C0
Pca CENT CF LAeOR CCST * 43.00
PtK CENT OF SOURCE COST =
0.0
PER CENT OF MAINTENANCE EQUIPPENT COST - 1CO.CC
MAINTENANN E POLICY-MAPGL
MCW-FPR
RUTFFL
CRKOTH
CRKFSLC
MOW-SW
BLAD-SW
RLAD-ORY
8LAO-WET
JuAIN-ýS
RGRVLSW SHLD-SW
1.00
-1.00
O000.00
5000.00
3.00
0.80
C.50
0.50
I.ou
1.00
1.0C
RtCALSThCTrICN SCHEDULE- RRLC
NO-UPGKAu
U
TuPCGOAPHY- TOPOG
77
NU. CF STATICNS
TTYPkClUt FLAT
ROLLINr
MCLNT
NSTA
100.00
77.00
-1.uQ
0.0
0.
ELEV.
ELEV.
STATION
ELEV.
STATION
ELEV.
STATION
SIATICN
cLEV.
STATICN
893.00
896.CO
50.00
888.00
110.00
888.00
140.00
880.00
200.00
430.00
R01."0
'u.uO0
887.00
20.00C
896.00
350.00
400.00
898.CC
888.CC
710.0a
898.00
460.OU
900.00
490.00
895.00
550.00
908.00
630.00
920.00C
864.00
880.CC
740.0u
888.00
840.00
898.00
760.00
826.CC
860.00
82 .00
940*.4
870.CO
1C50.00
843.00
1130.00
868.00
1300.00
835.00
1520.00
802.00
2080.00
1630.UU
820.CO
1720.00
806.00
1860.00
816.C00
2030.00
795.00
765.00
786.0C
773.00
i210.00
79C.00
2280.00
2360.00
2150.00
790.00
210A.uU
719.03
740.00
2830.00
714.00
2900.00
714.CC
3060.00
782.CO
2610.90
704.00
714.00
3570.00
730.00
3300.00
3530.C00
710.00
314u.ud
722.00
3220.00
714.00
702.00
7C4.00
3870.00
716.CC
3900.00
36io.00
708.00
36e0.00
3770.0C
700.00
713.00
718.00
4070.00
688.00
4100.CC
4000.00
3930.uU
705.CO
3970.0C
4580.00
60C.00
696.00
4460.00
71C.CO
712.00
4270.00
712.00
4350.00
4430.00
666.00
665.00
4900.00
675.CC
5CO0.00
470.00C
4840.00
664.00
680G.00
682.00
5280.00
5400.00
SUOu50.
682.00
5120.0C
646.00
5200.00
658.00
631.CC
636.CC
5960.0C
67C.00
5790.00
5460.40
614.00
5520.00
623.00
5610.00
626.00
608G.00
674.00
61CO.0C
670.00
SLIL * 6RuUNCCOVEP-COER.0CCV
CB0
EASY
NCORAL
CIFFICULT
6.uU
0.0
0.0
100.00
0.0
4.45
0.0
442U.U3
64C.00
Bolivian Base Scenario Data
Figure 22
114
SIDE-CL
20.00
THICK3
0.C
RUT-OTH
1.50
SUR ONT
0.0
DRAINAGE RcLATED CATA-CRAIN
LT-RAIN
WATR-BLUE IPPASS
AVERAIN
1.00
40.00
&.00
1.00
IGO
01STANCESoCCkSTRUCT
FLT-MEC
0.0
FLI-LCT
C.0
HAUL
I-BGR
10.00
HAULOIST
LAYERI
LAYER2
1.00
2.00
0.0
PAVEMENT
LAVER3
SHCLLOER
O.C
2.CO
MPAITENANCE
WATER
0.0
GRAVEL
2.CC
PATrc
0.0
CULVERTS
200.00
WCNSTAUCTIuh PROCUCTIVITIES + COSTS-PRLO
SITE PRIPAAATIOh
*ASY
O.u
SURROW
0.u
PAVEMENT
PFau
448.00
0.0
NCRPAL
0.0
HARC
0.15
LCOST
127.20
EOCOST
TRANSPORT
P'OC
LCOST
EMCOST
0.0
110.00
1057.00
TRANSPORT
LCOST
0.0
495.70
0.0
0.0
C.C
348.00
0.0
DRAANAGk
NO. JF CULVERTS
SCUST
WEIGIT
384.uU
55.CC
52s.wU
825.00
SOURCE
O.C
*
0.0
0.0
0.0
0.0
0.0
4955.70
854.40
7464.00
EOCCST
3446.4C
0.0
0.0
3446.4C
5.00
TCOST
0.02
0.02
t71.UO
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0.02
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210.C3
0.02
148..40
280.00
0.02
OIhkR CoMPjThENTS
ICuaT
2LAOCR
ITCTST
ILABCK
0.0
0.0
0.0
MAINTINANLL COSTS ANC PRCCUCTIVITIES-MUC
uCTORGO
TRALuR
DUMPTRK
BIlklS
7?.C0
8s.tC
86.00
1SU.uu
CLAbUk
ELCPER
FCREMAtI TCRIVER
13.4C
6.00O
6.uU
6.00
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CAýCOST
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0.0
,.0
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0.0
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DRIVER
GISCCST
DIESEL
0.0
6.00
0.0
a.Q.
0.0
6..J
6.Co
IhITIAL COST
MARKET
tCCjN.M
36U60.UU
54000.00
396G.W0
5760C.00
93*Lu.O, A44000.CO
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VE4TII
UCWEILLL
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3.0
04
TRACTOR
15.CC
PATMIX
C.0
WTRTRK
71.00
CJVSEAL
0.0
0.0
TIRE CC"T
MARKET
ECONCO
313.00
468.00
351.3C
576.00
1440.0'
2052.00
TCNWLS
0.45E 03
0.16E C4
0.20E
RCLLER
77.5C
LIQASIP
0.0
HRSEPMR
0.40E 02
0.14003
C.11E 03
VEPICLE
MARKET
ECONCP
9.7C
11.20
5.0C
9.40
26.10I
26.00
CARGO COST
ECINCM
MAkEtT
0.0
0.0
0.C
0.0
0.0
0.0
CHPVEHH
VEPWCTI
0.10E 0!
.T17E 01
J.20E Cl
0.139 01
0.15
11 J.24E 01
DSNSPEEC
0.12E 03
0.95E 02
O.50E 02
115
VEHHT
'IRCCEFF
FUELTYPE
0.18E G& 0.TIE-O1
0.0
X.C
0.19k Cl
C.24i-01
0.2SC Cl
C.34E-01
0.n
consideration the model needs to know; the haul distances
for construction materials; maintenance unit costs; and vehicle descriptions and prices (among other factors). It
sould also be noted that a road design is described under
the headings ROADWAY CROSS SECTION and ROADWAY DESIGN DATA.
This information is what the model must know before it
can
determine the costs of a road.
5.
Development and Selection of Staging Alternatives
This section discusses the problems involved in select-
ing a set of strategies for investigation and how they can
be "winnowed." from the large number of alternative designs
and staging strategies that do exist.
In order to reduce
the number of designs which require examination, the problem
is to distinguish within the continuum of all possible designs and staging strategies in such a way that 1) a representative number of alternatives is considered and 2) the
number of alternatives examined is small enough so that
undue amounts of time are not spent in computing their
associated costs.
The first parameter that can be used to narrow down
the investigation is that of pavement design.
There are
four types of surfaces generally used for low volume roads
--earth, gravel, surface treated, and bituminous or asphalt
concrete.
It is difficult to make meaningful distinctions
between closely related road designs for the earth and
116
gravel roads while using the HCM, with the exception that
regraveling will be required with less frequency on thicker
gravel roads.
However, regraveling has only a very slight
effect on total road transport costs and can be disregarded
during this discussion.
Also, a surface treated road is a
fairly well-defined design, with variations permitted only
in the design of the base and sub-base.
In contrast to the
limited variations found in these designs, however, asphalt
road designs can be found in far greater proliferation.
There do exist design techniques that can be used (AASHO,
RRL, Asphalt Institute, and local experience) to determine
a starting point for the initial investigation.
6.
Timing
Timing of reconstruction is obviously one of the most
important issues; the crucial question is: how sensitive are
the total costs to small changes in the timing of reconstruction--for example, changing the reconstruction interval
from every five to every six years.
The HCM has demonstrated
that for discount rates of twelve percent per year and less,
if reconstruction is performed anywhere within a four- or
five-year interval only small changes in total discounted
construction, maintenance, and vehicle operating costs occur.
For this reason a five-year interval for reconstruction is
considered appropriate during the initial investigation of
costs accruing to various strategies.
117
It should be noted
that because of the iterative approach used in finding the
optimal construction strategy, errors due to this somewhat
arbitrary interval choice will be minimized.
7~
Upgradings
This section will further delimit the alternate invest-
gation space by defining feasible strategies for reconstrucThese strategies are based on the premise that the
tion.
model user will wish to improve the quality of a road in
time, or to leave it
alone (subject to considerations of de-
terioration and maintenance.)
Thus there are only a limited
number of upgrading policies which can be implemented.
For
example, a gravel road can be upgraded to a surface treated
or paved surface, but a paved road can only receive an overlay.
Figure
9
shows the twenty-five feasible strategies
that can be derived using this philosophy.
An "S" as the
last letter indicated new construction and is used in any
but year one, or after the NULL option indicates an alignment change.
The alignment change option should be explained in more
detail.
The model offers the option of changing the align-
ment of the road during the design life.
Thus a road con-
structed with steep grades and sharp curvatures could be
flattened out some years after the initial construction.
Because of the great variety of situations in which this
118
type of reconstruction might be performed, it is difficult
to generalize about a good choice for this option.
However,
as the pruning rules in the previous chapter indicate, reconstruction on a new alignment may be appropriate if some
of the following conditions hold: the original road is on a
very steep alignment; there is a narrow right-of-way with
little room for expansion; traffic has grown at a high (ten
percent or more) per'year rate and delays due to slow, heavy
vehciles in the traffic stream are great; a suitable alternative alignment exists that does not unduly increase pointto-point distances.
It is recognized that these conditions
are not objectively defined and offer little practical guidance to
the model user.
Further research and use of the
HOM in the field may yield sufficient experience to formalize
these rules, which could then be incorporated into this work.
However, since the model is inexpensive enough in actual
use, such alternatives could be readily examined by the
model' s users.
8.
Maintenance
Previous studies (Alexander and Moavenzadeh (36, 38))
have indicated the importance of maintenance in the operation
of low volume roads.
The role of maintenance is essentially
to preserve the running surface and thereby reduce operating
and reconstruction costs.
The model offers the user the
choice of six maintenance policies plus whatever he may
119
devise for himself.
The results of several experiments with the HCM have
indicated that under conditions of high labor prices the
best policy in terms of total maintenance and user costs is
normal capital intensive, while if the shadow price of
foreign exchange is high, normal labor intensive appears to
be the best policy. If it is desired that road users pay
a greater proportion of road transport costs, then, of
course, poor maintenance policies could be used; if it is
desired that they pay a smaller proportion, excellent maintenance would be most appropriate.
It should be noted, how-
ever, that indications are that savings to the government
due to poor maintenance policies are considerably less than
the extra costs incurred by road users.
This may not be
true in contexts other than the Bolivia and Argentina
scenarios, though, and the model user is urged to test this
hypothesis by defining a staging strategy and examining the
costs accruing to it when each of the six maintenance policies is used in conjunction with the staging strategy.
In
many cases he should find that total costs are lowest when
normal or excellent maintenance is employed and that the
savings due to poorer maintenance are overshadowed by increased-user operating costs and the need (in some cases)
for earlier reconstruction.
Assuming for the moment that there is no alternate
120
alignment suitable for examination, we are left with twenty-five alternate strategies suitable for investigation.
This number can be further reduced by reference to the
pruning rules of the previous chapter.
For example,. assuming
that initial traffic conditions are those presented in Ta-.
ble 5
,
the pruning rules indicate that earth roads, and any
road that has an earth surface and is later upgraded, are
undesirable.
Thus, the number of alternatives to be investi-
gated has been reduced by a factor of two, with corresponding
reductions in direct computer costs.
The utility of using
the pruning rules and the consequent cost reductions must be
traded off against the knowledge that these pruning rules
have been based solely on two sets of factor prices and terrain data, and may very well be inaccurate under different
conditions.
Again, it is recommended that the user gain
familiarity with the model and modify-those areas of the
documentation that do not agree with his experience.
9.
Search for the Optimal Road
This section will discuss in some detail the procedure
to be followed in using the Highway Cost Model to select an
optimal road design within the limit of precision provided
by the HOM.
The reader should recognize that "optimal" is
used in the context of a local optima, that is, within the
decision space examined rather than a global optima which
121
vehicle class
elasticity
of demand
vehicles/day
~~r~~r~~~~~
growth rate
% per annum
~-----------------------~~
15
.012
15
.003
30
.003
Traffic Data Used in Bolivian Base Scenario
Table 5
122
would be the best of all possible roads.
No techniques are
known to exist that could find the latter.
For the purposes
of this examination, we shall continue to use the Bolivian
data, along with the traffic projections and construction
staging strategies already examined.
It is expected that
sufficient information will be presented to permit the
reader to use the HCM effectively and accurately.
The examination of the twenty-five alternate staging
strategies makes up the first iteration of the model.
Fig-
ure 23 shows the total discounted costs accruing to each of
these strategies and their relative rank.
The timing of reconstruction can cause significant
changes in cost.
In order to investigate these effects,
a second run was made.
The strategies chosen for this run
(see figure 24) were similar to the best strategies of
the previous run (numbers 11, 14, 18, 19, 22) except that
the timing of reconstruction for the staged alternatives
was altered by +2 and -3 years respectively.
The costs
accruing to these strategies are given in figure 25.
Ex-
amination of these costs shows that the altered alternatives
are more expensive than the original policies and should
not be chosen for implementation.
Since a change in timing has been shown to be ineffective in this case, the next issue to consider is the maintenance policy.
The third iteration answers the question
123
25
24
9
S23
0
O
O
OO
'-W
Ir
0
C2
S22
U
6r
4.1
9
6
20
19
_1.
Figure 23
Costs of the first
iteration
124
_
GRAVEL2S
SURFACES
S
--
ASPHALT
ASPHALTS
Year:
I
Staging Strategies for the Second
Iteration
Figure 24
125
Figure 25
210
200
190
Strategy
Costs of the Second Iteration
126
"will excellent or poor maintenance policy decrease the costs
accruing to these strategies?"
This can be investigated
by means of the input shown in figure 26.
The numbers fol-
lowing the design indicate the various maintenance policies,
ranging from capital intensive to labor intensive and from
poor to excellent.
The figure shows the costs due to each
of these maintenance strategies and indicates that an excellent capital intensive maintenance policy is the one to
select if the measure of effectiveness is lowest net present
worth.
10.
Continuing the Iteration
At this point the user should ask whether to continue
the search process or to halt it. There are two criteria
that can be used to make this decision.
The first is-"are
the expected costs of performing another run greater than
the expected reductions in costs due to finding a better
staging strategy?"
The second is "do you feel that this
strategy can be successfully implemented?"
If the answer
to either of these questions is "no", then the search pattern
should be extended, another iteration performed, and the
questions repeated.
11.
Length of the Analysis Period
The model user can choose this parameter on the basis
of several factors--for example, institutional requirements
127
#
1
2
3
4
5
6
Strategy Definition
Poor Capital Intensive
Normal Capital Intensive
Excellent Capital Intensive
Poor labor intensive
Normal Labor Intensive
Excellent Labor Intensive
21.2
0
o
0
o
o
021.o
4
.)
0
20.6
...
Mr
--r
·- pl
-- 40-
3
4
k--0
5
6
Strategy
Figure 26
Costs of the Third Iteration
128
such as those of A.I.D. or the World Bank.
The experience with the HCM indicates that the effect
of varying the length of the analysis period is very much
dependent on the context in which it is done.
For example,
extending the analysis horizon while examining gravel and
asphalt roads will have different effects on the relative
desirability of each, road depending upon the growth rates
of each vehicle class, thme Iterest
rate, the alignment
(particularly the average grade), and the traffic level.
Because of the multitude of factors involved in determining
the effects of changes.in the analysis horizon, no recommendations as to the sensitivity to this parameter can be
made.
However, it is suggested that the model user, upon
finding an optimal strategy, repeat the last iteration
while varying the "nalysis period plus and minus five years
to see the effect these changes have on the determination
of the optimal strategy.
12.
Effects of Uncertainty in Traffic Projections
This section will discuss the effects of uncertain
knowledge of future traffic levels on total costs, the
distribution of costs among users, the road agency, and the
optimal strategy for investment.
Uncertainty in traffic projections as used in this
report refers to the three factors used to describe traffic:
130
1) the number of vehicles in year one, 2) the elasticity of
demand, and 3) the annual growth rate, either in terms of
vehicles per year or percent per year.
For low volume
roads, and especially for penetration roads, most of these
factors will not be definitely known.
As variations from the estimates of these factors often
occur in practice, and frequently cause the effectiveness of
a road to be significantly diminished--a paved road, for example, being used by only thirty vehicles a day, or an earth
road carrying one hundred seventy vehicles a day--it is desirable to decrease as far as possible the effects of uncertainty in the parameters.
13.
Effects on Total Costs
As expected, the factor which had the greatest effect
on total costs was 'he growth rate.
The reason for this is
quite clearly the compound growth caused by constant percentage increases in traffic.
For example, if the estimated
yearly growth rate for one vehicle class is eight percent
while in reality it turns out to be only six percent, then
(assuming inelastic demand) after twenty years the total
traffic will be overestimated by approximately twenty-five
percent, while the number of vehicles using the road in year
twenty will be seventy percent of the original estimate.
Table. 6 , shows the costs and numbers of vehicles using the
Bolivian road under these conditions.
131
It should be noted
Vehicle Class
IniT
al
a
Traffic
Vehicles in Year 20
G=6-7
G=8/
Ratio
1
15
48
70
0.7
2
15
48
70
0.7
3,
30
96
140
0.7
Effect of Inaccurate
Growth Rates
Table 6
132
Sthat although the total discounted road user costs have not
shown a twenty-five percent change and while total costs are
even less sensitive, there is a significant change in both
categories.
The second factor that Jis significant here is the elasticity of demand.
Elasticity of demand is a measure of how
sensitive the number of vehicles using the road is to changes
in road user cost (for example, the cost reductions due to
running on a paved rather than a gravel surface).
In a sit-
uation with very elastic demand, total traffic would be considerably greater on a paved road after twenty years than
it would be on an earth or gravel road.
crease is,
ble
(The relative in-
of course, a function of the growth rate.)
Ta-
7 shows the effects of different elasticities of demand
on one class of ve.,icles for earth, gravel, and paved roads.
In order to compare alternative strategies when the
traffic demand function is elastic, the concept of willingness to pay was introduced.
Appendix B presents a brief
description of this concept and its use in strategy evaluation.
Willingness to pay, as Appendix B shows, makes it
possible to compare roads carrying different traffic volumes,
since willingness to pay calculations involve determining a
"base per kilometer cost" for each type of vehicle against
which all operating costs are measured.
If for a given road
and vehicle type the per kilometer operating costs are lower
133
Road Type
E=5%
E=1.2%
Ratio
mm-m-m-m-mmmmm-mmm--mm-mmmmmmm-------------------
Earth
19
20
Gravel
24
21
Paved
1.05
.88
30
22
.73
-----------------------------------------
Number of Vehicles in Year 20
for Two Demand Elasticities
Table 7
134
than the base cost, the HOM subtracts the incremental
willingness to pay from the total user costs. Similarly,
if the per kilometer operating costs are higher the incremental willingness to pay is added to the user costs. The
planner should recognize the necessity of using the same
base strategy (and thus the same base costs) in all of his
runs, or else he will introduce a bias into the succeeding
iterations.
14.
Initial Traffic Levels
This variable is perhaps as difficult to estimate as
any of the parameters discussed in this section, but fortunately its effects can be readily discerned.
The realtionship between total road user costs and
the initial number of vehicles is
Uc
=
K
i=1
aLNL
where a and N refer to a given class of vehicles operating
on a certain road type and maintained to a given standard.
Thus, if-the initial estimate of traffic is doubled, user
costs will also be doubled relative to the estimate.
should be noted that this is
It
only true for similar construc-
tion strategies, and that there will be a slight variation
due to faster deterioration of the road when it
is used by
heavier traffic and to the increased maintenance costs on
that road.
135
15.
Effects on the Optimal Strategy
As the previous discussion has indicated, uncertainty
in the planner's knowledge of future traffic conditions can
cause the estimated costs to differ significantly from the
costs which occur in actual practice.
Obviously such
changes will affect the choice of optimal investment strategy under many conditions, assuming that road user costs
are included in the measure of effectiveness used in evaluating competing costs.
It is for this reason that the HOCM offers the user the
option of specifying, during a single run, one or more sets
of initial traffic conditions so that he may 1) estimate
the probability of the realization of each set, 2) define
the properties of each set: elasticity, growth rate, and
initial traffic, and 3) see the costs accruing to each set
and the expected value of the costs computed by the formula
n
E(C) =
PiCi
i=1
where Pi is the probability of realizing traffic set i,
Ci is the costs accruing to set i, and n is the number of
sets of traffic.
Through this process the model user is given the opportunity to see how the optimal strategy varies with initial traffic properties.
Once this information has been
obtained, several procedures can be followed.
136
The simplest
procedure is to build the.optimal road as defined using
the expected costs determined from the equations presented
above.
Another approach would be to use that strategy
which is optimal under the most likely (that is, having
the highest probability of occurring) traffic set.
A third
procedure would be to select the strategy which has been
ranked first more frequently than any other alternative.
(If there is a tie for the greatest number of "firsts"
then the one of these which also has the greatest number
of "seconds" would be chosen, and so on.)
In addition to
these three selection procedures there are of course many
other techniques; but it is recommended that the first approach be used for the following reasons: 1) In specifying
the initial traffic sets and their probability of occurring,
the user is attempting to describe a cont;iauous distribution
of traffic using a small number of points.
In so doing it
is very unlikely that an accurate description has been made
because of human error and the incomplete data that must
be used in preparing estimates. 2) Over the long run, the
use of the "expected cost" best strategy will have the
highest benefits (this was established by Pratt at al. in
Statistical Decision Theory (54)). 3) The choice of a
strategy on the basis of other than the expected costs
implies that the user has not accurately assessed his estimates of the probability of occurrence of the traffic sets;
137
by choosing a different strategy from the one found using
expected costs he signifies that he does not believe his
original assessment of the probabilities.
4) Assuming
that the range of traffic conditions is not too great, a
similar strategy will probably be optimal for many of the
initial sets of traffic.
Using this approach, the model user can expect that
the optimal strategy will be cTlosely approximated by the
road he has chosen for construction, even though it may
not be identical to the optimal strategy under traffic conditions that do prevail.
If the traffic that does materialize is considerably
different from that which was expected, it may be worthwhile to use the model to estimate the costs which are incurred due to this new traffic and see how much the effectiveness of the link is reduced by the non-optimal design.
If the reduction in effectiveness is considerable, it may
be desirable to alter the design, either to the optimal
design for the observed traffic level or to a design close
to the optimal.
16.
Road User Benefits
During the previous discussion of the use of the
HCM the concept of benefits has only been discussed in conjunction with incremental willingness to pay.
It should
not be assumed, however, that it is being suggested that
138
roads be constructed solely on the basis of perceived
costs.
It is recognized that benefits will accrue to the
economy as a result of road construction--benefits which
are important factors in the decision to build a road.
This subject is not explicitly considered because of the
difficulty in defining, measuring, and evaluating the
benefits accruing to a road; the realization that these
benefits are very much a function of the use of the road,
the location, the products it carries, cannot be expressed
as a formal model.
To a limited extent, the incremental willingness to
pay is a surrogate for these unmeasured benefits, and it
is suggested that planners use the HCM in the early design
process to seek out three or four construction strategies
for further evaluation.
The techniques presented here are
designed for use at this stage of the design process; it
cannot be emphasized too heavily that they should not be
the basis of a final build-or-no-build decision.
The HCM
is a model with several well-defined areas requiring more
research, and others requiring more sophistication.
this reason, its estimates should be
clearcut role as estimates.
139
For
utilized only in a
Chapter Seven
Conclusion
The Highway Cost Model can be a highly effective tool,
providing fairly sophisticated planning for even the relatively inexperienced computer user.
In the tradition of
the "little black box", the model is able to perform this
feat by internalizing its complexities.
An example of the mcael's internalized complexity can
be seen in the communications section of the program.
This
subroutine can take as input a list of the model user's
staging strategies, which are written in a form close to
conventional English; for example, the user would specify
a two-lane earth road by writing "EARTH2S".
This list
would then be converted by the subroutine into a two-dimensional array which would then be utilized by the network
routine to decide what actions NETWRK should take.
ure 27
As fig-
demonstrates, the communications subroutine can
take a list of staging strategies such as the one shown in
the top half of the figure and convert it into the array
shown in the bottom half of the figure.
The translation
is accomplished by several hundred FORTRAN statements, which
search a dictionary for the meaning of the user's commands
and simultaneously keep track of the position of each of
these commands in both time and space.
STRAT can also, if
necessary, redefine the dictionary; if local conditions (for
140
RECONSTRUCTION STRATEGIES
2.0
0.
EARTH2S
0.
0.0
0.
0.0
0.0 .0.
0.0
0.
0.
0.0
0.
0.0
0.0
5.
0.0
5.
0.0
5.
GRAVEL2S
0.
2.0
0.0
0.
0.
0.0
0.0
3.
0.0
0.
0.0
5.,
5.
0.0
0.
2.0
SURFACES
0.0
0.
0.
0.0
5.
0.0
2.0
0.
ASPHALTS
0.0
0.
0.0
0.
0.0
5.
GRAVEL2
SURFACE
ASPHALT
'
SURFACE
ASPHALT
ASPHALT
ASPFRNW
RECGNSTRUC TION STRATEGIES
TYPE MAINT. POLICY
YEAR
E
2.0000
1.
3.
2.0000
15.
9.
2
2.0000
3
15.
1C.
4
2.0000
15.
11.
2.0000
5
10.
9.
2.0000
10.
10.
2.0000
7
10.
11.
S.
99.
2.0000
8
2.0000
5.
9
10.
5.
11.
2.0000
10
2.0000
1.
5.
11
15.
i.
2.0000
12
2.0000
15.
11.
i.1
2.0000
10.
10.
14
10.
2.0000
11.
15
2.0000
16
5.
10.
7
2.0000
5.
11.
.
2.0000
1.
6.
15.
11.
2.0000
19
IC.
11.
2.0000
-1
2.0000
5.
11.
2.0000
1.
7.
22
2.0000
15.
12.
23
2.0000
24
10.
12.
0.0
5.
12.
25
NUMB EH
YEAR
OF
NuDES
STRATEGY
15
10
5
1
15
£1
11
15
10
5
.15
10
5
GRAVEL2
SURFACE
ASPHALT
SURFACE
ASP-ALT
ASPHALT
ASPH RNW
0.0
0.0
0.0
0.0
2.0
2.0
2.0
0.0
0,0
0.0
0.0
0.0
0.0
2.0
2.0
0.0
0.0
0.0
0.0
2.0
0.0
0.0
0.0
2.0
0.0
0.
15.
15.
15.
0.
0.
0.
0.
0.
0.
0.
15.
0.
0.
0.
0.
0.
15.
0.
0,
0.
15.
0.
0.
GRAVEL2
SURFACE
ASPHALT
SURFACE
ASPHALT
ASPHALT
ASPHRIh
STRATEGY
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
IS
13
BRANCHES
3
3
1.
10l
45
0.
0.0
0.0
0.
0.0
0.
0.0
0.
0.01 10.
0.0 10.
0.0 10.
2.0
0.
2.0
0.
2.0
0.
0,0
0.
0.0
0.
0.0
0.
0.0 10.
0.0 10.
2.0
0.
0.
2.0
0.0
0.
0.
0.0
0.0 10.
2.0
0.
0.
0.0
0.0
0.
0.0 10.
0.0
0.
Ad
22
18
22
3
3
2
2
2
1
1
1
1
.Action of the Communication
Subroutine
22
Figure 27
141
0.0
2.0
2.0
2.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
2.0
2.0
0.0
0.0
0.0
0.0
0.C
2.0
C.0
O.C
0.0
2.0
0.0
C.C
example, very strong subsoils) exist, the model user can
tell the model to remove certain road designs from the
dictionary, and replace them with designs he feels are more
appropriate.
In addition to being simple, the model also makes allowances for the inexperienced user by being self-checking;
if the model user specifies staging strategies incorrectly
the model will bring a message to this effect, and will not
execute the program at this time.
types a card saying, "15GRAVEL2
respond by saying, "STRATEGY
For example, if the user
10EARTH2S,"
the model will
1 IS SPECIFIED INCORRECTLY."
But the model does not seek to eliminate the'user; on
the contrary, it asks for his skill, knowledge, and experience as it searches for the best use
can allocate his funds and energies.
to which the planner
For -xample, the
model user is asked to define the staging strategies which
he feels are appropriate to the road under consideration,
and to evaluate each of these strategies.
After evaluating
this first iteration, he is then asked to alter the best
strategies in a way that he feels will make them more effective; the model is thus at all times benefiting from the
user's practical experience and his knowledge of the area,
rather than merely seeking on its own some purely theoretical solution.
The HCM is a modest program; it does not overreach its
142
own limitations or inflate its estimates into hard-and-fast
predictions.
This can be especially valuable in an uncer-
tain situation.
It is hoped that further implementation
of the model (see Appendix A) will make it possible for the
model to increase its precision without sacrificing its
flexibility.
In view of these advantages, it is suggested with
some confidence that the HCM is an effective technique,
which will be of service to planners in helping them to
allocate scare resources to road projects, thus aiding in
the optimal economic development of emerging nations.
143
REFERENCES
144
REFERENCES
1.
Bauman, Richard D., An Analytical Method to Determine
Highway Design and Forecast ' Stage Construction Levels
'in an Emerging Country, Ph.D. Thesis, Arizona State
University, 1968.
2.
Thompson, C.B., Transportation Coordination, Economic
Section, Federal Public Works Department, Lagos,
Nigeria, July 1959.
3.
Bonney, R.S.P., The Relationships Between Road Building
and Economic and Social Development in Sabah, Part I:
Roads and Road Traffic, Lab. Note No. LN 519, Department of Scientific and Industrial Research, Road
Research Laboratory, February 1964, 8.
4.
A Guide to Highway Design Standards, International Bank
for Reconstruction and Development, Washington, D.C.
(June 1957) p. 69.
5.
A Guide to the Structural Design of Bituminous-Surfaced
Roads in Tropical and Sub-Tropical Countries, Road
Research Laboratory, Road Note 31, London; HMSO,
2nd Edition, 1966.
6.
Thickness Design, The Asphalt Institute, 8th Edition,
December 1969.
7.
Thrower, E.C., and Burt, M.E., A Study of the Economics
of Stage Construction for Road Pavements, RRL Report
LR 286, 1969.
8.
Winfrey, Robley, "Cost Comparisons of Four-Lane vs.
Stage Construction of Interstate Highway," HRBB #306,
1961, pp. 64.
9.
Hewit, George G, "Asphalt Versus Gravel Roads in
Developing Countries," World Highways, December 1969,
Vol. 20, No. 12, p. 14.
10. Mori, Yasuo, "A Highway Investment Planning Model: An
Application of Dynamic Programming", Unpublished M.S.
Thesis, Department of Civil Engineering, M.I.T.,
Cambridge, Mass. 1968.
11. Stafford, Joseph H. and Richard de Neufville, Engineering
Systems Analysis, Chapter 9: "Choosing Among Investment Alternatives," M.I.T., Cambridge, Mass., August
1970.
145
12.
Marglin, Stephen A, Approaches to Dynamic Investment
Planning, North Holland Publishing Co., Amsterdam,
1963.
13.
Manne, Alan S., Editor,' Investments for Capacity Expansion, The M.I.T. Press, Cambridge, 1967.
14.
Schezer, Herbert E., Analytibal Models for Managerial
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15.
Haussmann, Fred, Operation Research Technique for
Capital Investment, John Wiley & Sons, Inc., New
York, 1968.
16.
Ochoa-Rosso, Felipe, "Application of Discrete Optimization Techniques to Capital Investment and Network
Synthesis Problems," Sc.D. Thesis, M.I.T., Cambridge,
Mass.
17.
Gulbrandsen, Odd, "Optimal Priority Rating of Resource
Allocation by Dynamic Programming," Institute of
Transport Economy, Royal Norwegian Council for
Scientific, Industrial Research, Oslo.
18.
Hillier, Frederick S., and Lieberman, Gerald J.,
Introduction to Operation Research, Holden-Day, Inc.,
San Francisco, 1967.
19.
Winfrey, Robley, "Cost Comparison of Four-Lane vs.
Stage Construction on Interstate Highways," Highway
Research Board Bulletin No. 306, p. 64-80.
20.
McKean, Roland N., Public Spending, McGraw-Hill Book
Company, New York, 1968.
21.
Hansmann, Fred, "Operation Research in National Planning
of Underdeveloped Countries," Operations Research,
Vol. 9, 1961, p. 230-244.
22.
Reutlinger, Schlomo, Techniques for Project Appraised
Under Uncertainty, World Bank Staff Occasional Papers,
No. 10, IBRD, Washington, D.C., 1970.
23.
Bierman, Harold, Jr., and Smidt, Seymour Smidt, The
Capital Budgeting Decision, The MacMillan Company
New York, 1966.
24.
Dean, Joel, Capital Budgeting: Top Management Policy on
Plant Equipment and Product Development, Columbia
University Press, New York 1969.
146
25.
Cord,J., "A Method for Allocating funds to Investment Projects Which
are Subject to Uncertainty," Management Science 10, No. 2
235-241, Jan. 64.
26.
Hansman,F., "Operations Research in National Planning of
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27.
Nashlund, Biertel, and Whinston, "A Model of Multiperiod
Investment Under Uncertainty," Management Science, Vol. 8
184-200, 1964.
28.
Kalaba, R.E., and Juncora, "Optimal Design and Utilization of
Communication Networks," Management Science, Vol. 3,33-44,1956.
29.
Lorie, J. and Savage, "Three Problems in Capital Rationing,"
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30.
Hillier,F.S., "The Derivation of Probabilistic Information
for the Evaluation of Risky Investments," Mgt. Science,
Vol. 9, 443-457, 1963.
31.
Raiffa,H., Preferences for Multi-Attributed Alternatives,
Memorandum RM-5868-DOT/RC, The Rand Corp.., Santa Monica,
April 1969.
32.
Pecknold,W.,"The Evaluation of Transport Systems," Unpublished
Ph. D. Thesis, M.I.T. Dept. of Civil Engineering, Sept. 1970.
33.
Lack, G.N.T., et al, "A Model for the Economic Evaluation of
Rural Road Investments," Paper No. 488, presented at the
Fourth Conference of the Australian Road Research Board,
Melbourne, August 1968.
34.
Woods,K.B., editor, Highway Engineering Handbook, McGraw-Hill
Book Co., Inc., New York, 1960.
35.
Roberts, P.O.,"Transport Planning Models for Developing Countries,"
Ph. D. Thesis, Northwestern University, June 1966.
36.
Alexander, J.A., "An Approach for Integrating Highway Maintenance
Into the Design Process," Ph. D. Thesis, M.I.T. Dept. of
Civil Engineering,.Sept. 1970.
37.
Manheim, M.L. and Ruiter and Bhatt, Search and'Choice in Transport
Systems Planning: Summary Report, M.I.T. Dept. of Civil Engineering
Report #R68-40, 1968.
38.
Moavenzadeh, F. et al., Highway Design Study: Final Report,
CLM/Systems Inc., Cambridge, 1970.
147
39.
Daniel, Mann, Johnson and Mendenhall et al., Bolivia Transport
Survey, Los Angeles and La Paz, 1968.
40.
U.N. Dept. of Economic and Social Affairs, " Capital Intensity
and Costs in Earth Moving Operations,"
Bulletin No. 3, March 1960.
41.
Shaner W,, Economic Evaluation of Investments in Agricultural
'Penetration Roads in Developing Countries: A Case Study of
. The Tingo-Maria Tocada Project in Peru, Stanford Program
on Engineering Economic Planning, Report Ee 22,August 1966.
42.
Steiner, H.M., Criteria for Planning Rural Roads in a Developing
Country: The Case of Mexico, Stanford Program on Engineering
Economic Systems, Report Ee 17, August 1965.
43.
Sen, A.K., Choice of Technique: An Aspect of the Theory of
Planned Economic Development, Second Edition, New York,
Kelley , 1965.
44.
Harral, C., The Preparation and Evaluation of Transport Projects,
WAshington, The Brookings Institute.
45.
Midler, J.L., " Investment in Network Expansion Under Uncertainty,"
Transportation Research,Vol. 4, 267-280, 1970.
46.
Burns, R.E., "Transport Planning: Selection of Analytical Techniques," J. of Transportation Economics, 306-321, Sept 1969.
47.
Odier, L., The Economic Benefits of Road Construction and
Improvement, Estoup, Paris,1967.
48.
Haefele, E.T., editor, Transport and National Goals,
Institution, Washington, D.C., 1969.
49.
Raiffa, H.,Decision Analysis, Reading, Addison Wesley, 1968.
50.
Lago, A.M. "Intercity Highway Transportation Cost Functions in
Underdeveloped Countries," Ph. D. Thesis Harvard University, 1966.
51.
de Weille, J., "Quantification of Road User Savings," I.B.R.;D.,
World Bank Staff Paper no. 2, Washington, D.C., 1966.
52.
Soux, A.H., "Right-of-Way Preparation Cost," Unreleased study
prepared by TRW Systems for the Office of High Speed Ground
Transportation, U.S. Dept. of .Transportation, Contract C353-66
(Neg) 1968.
148
The Brookings
53.
Charles River.Associates,. Inc,, Choice of Transport Technology
Under Varying Factor Endowments in Less Developed Countries,
Prepared for the Office of the Assistant Secretary for Policy
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Washington, D.C., June 1970.
54.
Pratt, J.W-, Raiffa, and Schlaifer, Introduction to Statistical
Decision Theory, New York, McGraw Hill Book Co., 1965.
55.
Midler, J.L., "Investment in Network Planning Under Uncertainty,"
Transportation Research, Vol 4, 267-280, 1970.
56.
Pritsker, A.A.B., GERT, Graphical Evaluation and Review Technique,
NASA Research Contract no..NASr-21, to the Rand Corp, Santa
Monica, April 1966.
57.
Moavenzadeh,F. et al., The Highway Cost Model,
of Civil Engineering, Cambridge, March 1972.
58.
Soberman, R.M., Transport Technology for Developing Regions,
M.I.T. Press, Cambridge 1966.
59.
Taylor, M.H., Network Planning in Management Control Systems,
Hutchinson Educational Limited, London 1970.
60.
Wagner,H.M., Principles of
Englewood Cliffs, 1969.
61.
Vance, L.M.
Operations Research,
M.I.T. Dept.
Prentice-Hall,
A Ro d Maintenance Cost Model, University of
California , 1970.
62.
Louis Berger, Inc., Argentina National Route 14 Technical Economic
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East Orange, N.J. 1968.
63.
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64.
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149
APPENDICES
A. Recommendations for Further Work
B.
Willingness to Pay
C.
Argentina And Bolivia Data
D. The Earthwork Models
E. Listing of the Highway Cost Model
150
Appendix A
Recommendations for Further Work
Although the Highway Cost Model has been used extensively in analyses of Argentine and Bolivian road projects,
it has not yet been used during the actual planning of a
low-volume road in a developing nation.
It is suggested
that the HCM be used in the preliminary design stages of an
appropriate road.
Because it will be desirable to compare
the effectiveness of the HCM with standard practices, perhaps the best approach would be to perform parallel analyses
using both approaches.
If,
after the analysis is complete,
significant variations are found to exist between.the solutions, it is recommended that the user reconsider carefully
the assumptions which were made by the model and the engineering analyst who is using standard practice, and the
planner should then attempt to reconcile the differences
by modifying these assumptions where necessary.
Additionally, the HCM could be modified to operate in
an interactive model om a time sharing system.
This com-
paratively simple modification would make the planner an
even more active force in seeking an optimal investment
strategy and would probably decrease both the time and cost
necessary to find the best strategy.
If. field testing demonstrates that the HCM is useful
in this context, it is recommended that further work be
151
performed to determine the accuracy of some of the more
important relationships derived during the sensitivity
analysis (DOT(57)), most particularly the relationship
between velocity and road roughness.
Also of importance is
the problem of determining the culvert and drainage requirements and the relationship between frequency of blading
unsurfaced roads and the observed roughness in inches per
mile.
152
Appendix B
Willingness to Pay*
A short discussion of the supply and demand relationships of traffic will be used to explain the concept of
willingness to pay and its use in strategy evaluation.
The idealized demand curve shown in figure 28 as CD
indicates the number of vehicles that will travel between
two points as a function of the user's perceived price of
travel.
The supply curves for two strategies are labeled 1 and
2.
These represent the perceived cost the user must pay
(perceived user cost) as a-function of traffic volume for
each strategy.
For strategy 1, the supply and demand curves
intersect at point E.
Thus V1 vehicles use the road and
each will have to pay the price P 1 in user costs.
results in a total cost to users of (P 1 )(V 1 ).
resented by the area GEHO in figure 28 .
This
This is rep-
However, by defini-
tion, the demand curve is a representation of willingness to
pay.
Most of the users in volume V 1 would have been willing
to pay more than the actual price P 1.
The last user to
make up the volume V1 is represented in the demand curve at
point E. 'He paid exactly what the trip was worth to him.
*This material is appended courtesy of its author,
John Alexander.
153
change in consumer surplus
C
r:
change in willingness to pay
GI.
?I
,
I
i
,T~4A
I ..
-4
I
strategy 1
'-tr
tpo'v
I
"""~~6~
I
I
I
I
--
6 |.
r:$
I
-
Vt
V,
Number of Vehicles
Definition of Willingness to Pay
Figure 28
154
~D
All the other users paid less than the trips were worth to
them.
The price they would have been willing to pay is
represented by the portion of the demand curve between E
and C.
Presumably, the vehicle that wanted to use the road
the most would have been willing to pay up to price Po.
The difference between the total that users would have
been willing to pay, CEHO, and what they actually paid,
GEHO, is called consumer surplus, area CEG.
Since this
is a savings to the users of the system, it is usually considered a user benefit in economic analysis.
If the same procedure is followed through for strategy
2, the user cost paid is represented by area FJOI, willingness to pay is area CFJO,
and the consumer surplus is area
CFI.
When comparing alternative strategies, the analyst is
interested in the differences in costs and benefits.
In
the example, strategy 2 can be considered to have a net
user benefit relative to strategy 1 equal to the change in
consumer surplus.
in figure 28 .
This is shown as the shaded area EFIG
The change in consumer surplus is used as
the measure of net road user benefit for this study.
Change in consumer surplus, EFIG, is the difference
between areas GEFJO and FJOI.
FJOI represents
road user cost paid for strategy i plus EFJH.
the total
Areas CE0O
and CFJO have been shown to represent the total amounts
155
that users are willing to pay at prices PI and P 2 respectively.
to pay,
EFJH is thus called the change in total willingness
when going from strategy 1 to strategy 2. There-
fore change in consumer surplus between two alternative
strategies is
0CSij
or
'ACSij
= UCi + WTPij - UCj
= UCi - (UCj
- WTPij)
where
ACSij = change in consumer surplus when changing
from strategy i to strategy j
UCi = total user cost for strategy i
UCj = total user cost for strategy j
AWTPij = change in willingness to pay when changing
from strategy i to strategy j.
As the previous section has suggested, the incremental
willingness to pay increases in absolute value with increases
in the elasticity of demand.
As it can be considered a cost,
it will affect the total costs of the road in question and
make comparisons between alternate strategies slightly more
complex and meaningful than they might otherwise be.
For the Bolivian traffic data previously presented
(see page
HCM .
) Table 7
shows the costs as calculated by the
By comparing the column labelled "Ratio" in both
tables it can be seen that for both demand curves costs are
proportional to the number of vehicles using the road for
1 56
any single road type.
However, slight differences do exist
and these are caused by the incremental willingness to pay
being different for the two demand curves. (Alexander(36))
157
Appendix C
Argentina and Bolivia Data
The following illustrations present a reproduction
of the input data to the Highway Cost Model as echoed
and annotated by the HCM of the base scenario for
Argentina and Bolivia respectively.
158
MAINTENANCE
OUTPUT SWITCHES FOR THIS RUN ARE CONSTRUCTION 0
0
USFr 0
OUTPUT IS PRINTED FOR YEARS THAT ARF A MULTIPLF OF 70 UNLESS THIS NUMRFP 1 IS POSITIVF
INITIAL TRAFFIC CrNDITIONS ASSOCIATED WITH THIS
THE TRAFFIC GROWTH SWITCH IS -1 AND THERE ARE 4 SETS OF
RUN 159
GATF
PROJECT
2/24/77
ARGENTINA DATA
ALIGNMENT DATA-ALIGN
LENGTH
DEG-CURVE
20.00
0.10
PROFILE DATA- PRCF
TYPE-SWITCH AVE-GRADE MAX-GRADE NO-VPIS
-1.00
0.44
3.13
15.00
VPI STA
VPI ELFV VPI STA
VPI ELFV VPI STA
VoE FL9V
-TA
VPI FLFV VPI STA
VPI FLEV
52750.00
39.30 93900.00
32.30 9"st.0C
11.60
17020.*0 24.00
9200.00
T9.6R
59700.00
19.70 61000.00
21.4)
62710.CC
19.•6
21.40 64700.00
R.96
66900.00
10.07 6P450.OC
19.94 70900.00
10
.?!
11&R7I
7oEp
77900.00
25.90
ROADWAY CROSS SECTIONIHOPIaINTALI-TEMPL
WIDTH
SLOPE
SHLD-WD
SHLn-SL
OTH-WO
0nT-S7I TH-1
TI-'L
CUT-SL
FILL-SL
PAVF-WT
4.50
2.25
0.03
C.82
0.25
1.00
.3
1.CO
0.75
1.50
DESIGN DATA(VERTICAL)-PAVE
THICK2
PAVE-CD
LAYFRS
MAT-TPE
THICKNESS
THICK
THICK
SHL50-TPF
THTCKI
3.0
2.00
3.00
4.00
0.15
0.0
0.0
0.0
0.0
2.00
0.18
ECONIMIC OATA
NO OF PERI.DS,0ISC. RATE, NO OF VEHICLE TYPFS
20
7.00
5
FOREIGN RATE CF EXCHANGE
1 PESOS
.
0.00103 OCLLARS
PERCENTAGE OF COSTS THAT C•pGINATE FROM 9RFIGN SrI5PCE.
PER CENT OF VEHICLE CnST
8 0.'),
EpEPC'T nF FUFL fOST - 70.PCPcP CENT OF TIrF CPST = 90.00
PFO CENT OF LARPR CCST .
0.0
PEP C9NT OF CONSTRUCTION FCUIIPMENT COST = 0o1.I
2..00
pOR CENT nF MAINTENANCE EOP)IPMENT COST = og.nn
PER CKNT OF SURCF COST *
MAINTENANCF POLICY-MAPnL
n
DRAIN-SW RPRVLSW SHtD-SW
MOW-SW
RLAT-SW
SLA0-ORY RLA0-WFT
UOW-FRO
RUTFrt
rPKnTH
rRKCSL
1.00
1.00.0
000.00
9000.00
3.00
.eC
0.950
1.50
RECONSTRUCTION SCHEDULF- PFRL
NO-UPGRAO
VPI
F411).00
ROADWAY
7,0
MAT-TPF
MAT-TPE
TOPOGRAPHY- TOFCG
Nn. OF STATICNS
20
NSTA
TYPECOOE
FLAT
RGLLING
MOUNT
26.00
-1.00
100.00
0.0
0.1
STAT ION
FLEV.
ELFV.
STATICN
STAT ION
STATION
ELFV.
STATION
ELEV.
FLFV.
;7250.00
'1.90
30.01 59000.00
52750.00
30.30 93900.00
6l,65. On
16.70
29.6
20.53
700a0.00
24.70 rQ701.00
29.90 58200.10
59600.00
57800.00
19.50
17.•0 60790.00
60500.00
19.00 '1000.00
272.6 61075.00
A
son.o('
21.60
0.00
69450.00
6or7l. O0
M.01) 65900.00
19.60 4
10OC.00
63600.00
70.57
716n. O00
0. O
70000.00oc
69500.00
15.90 70000.00
22.00 70400.00
728o0.00
29.60
SOIL * GRTUNDCCVER-CR9OGRCV
T
01FFICUL
CBR
EASY
NIPMAL
0.0
30.00C
7C.00
6.00
DRAINAGE RFLATFD OATA-nRAIN
FLT-MEO
FLT-LGT
WATR-RLOE
IMPASS
AVERAIN
120.00
0.0
1.00
100
I nn
1.00
HAUL DISTANCESCCNSTRUTTICN
PAVFMFNT
MAINTFCANCF
LAYFR3
SHnULEFR
WATFR
GRAVFL
OATOH
CtJLVFRTS
X-BOR
HAULDIST
IATER1
LAYER2
147.00
40.00
0.0
390.00
10.00
3f.00
644.00
2.00
1'.0o
CONSTRUCTICN PRCCUCTIVITIES + COSTS-PROD
SITE PREPARATIC1
I
Tn;T cornT0
HARE
NORMAl
EASY
MT-RAIN
380.00
Argentine Base Scenario Data
Figure 29
159
SITF-CL
?0.00
THICKR
0.0
RUJT-0TH
1.n
S'
*NT
1.0
0.20
20.36
0.50
0.40
EARTHWORK
TRANSPORT
BORROW
PROD
LCOST
1.26
0.06
250.00C
95.94
PAVFMENT
PROD
SOURCE
TRANSPORT
LCOST
400.00
1.86
0.00
67.52
0.01
163.00
22.30
96.23
387.00
65.70
0.0
151.61
163.00
22.30
0.01
96.23
DRAINAGE
NO. OF CULVERTS =
3.00
SCOST
WEIGHT
Tr7OS
67.10
55.00
0.00
107.41
110.00
0.00
168.37
160.00
0.00
OTHER COMPONENTS
XTCOST
SLABOR
YTCnST
TLAPOP
0.0
0.0
0.0
0.0
MAINTENANCE COSTS ANO PPCOUCTIVITIES-MUC
BITDIS
DUMPTRK
TRALDR
MOTORG)
4.30
15.05
25.00
23.6,
CLABOR
ECOPER
FOREMAN T0RIVFQ
2.65
5.80
6.70
4.8R
DIESELFUEL GRCCST
GASCOST WATERC
0.16
1.00
C.37
3.0
USER COSTSFCCN. AND MARKET- FCONn,MAPK
LABORC
DRIVER
GASCOST
OIES0 L
1.50
1.9q
C.1R
0.15
3.00
.90q
0.37
0.16
TIRF COST
INITIAL COST
FCCNOM
MARKET
FCONIM
MARKET
1C000.00 15000C.00
87.00
130.00
11000.00
160CC.00
q7.5C
160.on
26000.00 400C.00
400.00
r70.00
41rC.O0 63C000.00
Rg8.00
960.01
535.CC
790.00
79000.00 112rCC.00
VEHICLE OATA- VFF
OFWEILLE
VEHhT
WTDPWLS HRSEP P
0.10E 01 0.10E C4 0.60E 03 0.45E 07
C.20E 01 0.30F 04
0.15E 04 3.10F 03
0.1OF 01 0.13E CS 0.50E 04 0.1IF 03
0.53F 01
0.24F nq 0.11E 05
0.12F 03
0.40E 01
0.50F 04 0.3CE 04 0.10E 33
63.40
EOCOST
417.34
EOCOST
147.20
207.77
451.16
207.77
ROLLER
TRACYn
wTRTPK
PATwIX
'7.25
rnvSFAL
1.00
q.68
L TOAHP
0.16
VEHICLe C1ST
PCONCM
2.7C
1.40
7.23
7. oq
7.00
')SNSPEFP
0n.5FC2
C.O9F 02
C.75F 02
C.6KF C2
0.79E 02
160
MARKFT
3.10
1.50
7.25
8.10
7.10
CARGO COST
FCONOM
MAPYFT
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0(
0.0
CHPVHH
0.0
0.0
0.10F 01
0.10F 01
0.10E 01
VrHWDTH
VFHHT
AIRCPFC
C
1I 0.19E ri
0.20E CI 0.72E 01
0.17F-01
0.24F-01
O.23F 01
0.25F-01
0.27F-01
0.1PF
0.37F 01
0.?9F 01
n.24F 01
0.24E 01 0.16'F 01
0.27-rl
FUEL TYPE
0. 3
,3.0
0. ,
0.10C 01
O.10
01
OUTPUT SWITCHES FOR THIS RUN ARE CCNSTRUCTION 0
PAINTENANCE 0
USA
r.
I IS POSITIVE
OUTPUT 15 PRINTED FOR YEARS THAT ARE A MULTIPLE CF 20 UNLESS THIS
INITIAL TRAFFIC CONOITIONS ASSOCIATED WITH THIS
THE TRAFFI. GROWTH SbITCH IS -1 AND THERE ARE 3 SETS OF
MU1MER
,
CATE O/ 0
RUN 170
PRCJECT
0
BULIVAA TkST OF 25 YEAR ANALYSIS
ALIGNMENT DATA-ALIGN
LENGTH
uEG-CLRVE
6.10
15.00
PKOFILE DATA- PPCF
TYPE-SkITCH AVE-GRADE MAX-GRADE NO-VPIS
-1.00
6.72
9.29
15.00
VPt ELEV
VPI STA
VPI ELEV VPI STA
VP! ELEV
VPI STA
VPI STA
VPI ELEV VPI STA
VPI ELEV
0.0
896.00
140.00
886.00
600.00
9Cc.ou
107).00
835.Co
2100.00
790.00
d900.uu
720.003
3140.00
722.00
3660.00
702.C0
319.09)
714.CC
4100.00
700.00
4270.00
712.00
4680.00
680.00
4900.00
672.0c0 5520.C
610.00
410O.00
67C.00
muADVAY ChuSS SECTONIhHCRIZONTALI-TEPPL
WIDTH
SLEPE
SHLD-hD
SHLD-SL
DTH-hD
CTH-SL
:"-bO
DTH-SL
CUT-SL
FILL-SL
PAVE-hC
SIDE-CL
d.45
0.03
0.82
0.25
1.00
2.01,
3,
i.CC
C.75
1.50
4.!0
20.00
ROIAIWAY UOcIGN DATA(VERTICAL)-PAVE
SHLC-TPE
THICKJ
THICK2
THICK3
PAVE-CU
LAYERS
MAT-TPE THICKNESS MAT-TPE
THICK
W*T-'PE
THICK
2.u.
3.00
4.00
0.18
O.C
0.0
.
.0
.C
2.CC
0.18
0.0
D.C
ACONUMIC
,ATA
hu OF PcARIQJS~OISC. RATE, NO OF VEmICLE TYPES
25
6.CO
3
FL~nixlu RATE CF EXCHANGE
SPESu
0.09330 DCLLARS
PEMCkNTAuE 3F COSTS ThAT CAIGINATE FPCM FOREIGN SCURCES
PERR CENT CF FUEL CCST 80.00
P0a CENT CF VEFICLE COST 70.OCFER CENT CF TIME CCST *
80.0C
PF. CENT CF LAFCR CCST * 43.00
PEIR CENT CF CONSTRUtCTION EQUIPMFNT CCST = IC0O.C
PsK CENT OF SOURCE CCST
0O.0
PElR CENT OF MAINTENANCE
EQUIPPENT CCST * ICO.CC
MAINTENANL" POLICV-MAPCL
MCW-FRQ
RUTFFL
CKCOTH
CRKFSLC
RUT-OTH
RLAD-ORY
BLAD-WET
UiAIN-ad RGRVLSW SHLD-SW
MOW-SW
BLAD-S.
100O.C.
5000.00
3.00
0.80
C.50
0.50
1.50
1.0C
1.00
-1.00
L u*
1.00
kmC•iNSTkdJCICN SCFEDULE- RALC
NU-UpfGatu
TuPCGRAPHY- TOPOG
77
NO. CF STAfICNS
NSTA
TYPkCubU
FLAT
ROLLING
MCONT
100.00
77.00
-l.uu
0.0
0.0
STATION
SIATIC
CLEV.
STATICN
ELEV.
ELEV.
STATION
EL EV.
STATION
880.CC
896.C0
50.00
881.00
110.00
888.00
140.00
200.00
430.00
80C.CC
gSu.uO
887.00
20.00C
896.00
350.00
400.3C
848.CC
888.CC
46.0UU
900.00
490.00
895.00
550.00
908.00
630.00
710.CC
880.CC
74J.Ou
898.00
760.00
888.00
840.00
886.CC
860.00
920.00
94u.u,
870.00
IC50.0C
843.00
1130.00
668.00
1300.00
835.00
1520.00
2080.00
1630.uu
820.00
1720.00
806.00
1860.C0
816.CO
2030.00
795.CC
778.00
a210.00
790.00
2280.00
786.CC
2360.CC
JAO.uU
790.00
2150.0C
714.CC
740.00
2830.00
714.00
2900.00
3060.C00
442u.u3
782.C0
2610.3C
714.00
3530.10
710.00
3570.00
314ueuj
722.00
3220.00
730.00
3300.00
7C4.00
3870.00
716.CC
3000.00
3770.OC
3640.00
738.00
3610.00
702.00
710.00
4000.00
718.00
4070.00
4100.CC
688.00.
3930.ijU
705.CO
3970.00
696.00
4460.00
71C.CC
4580.0C
4270.00
712.00
4350.0C
712.00
4430.00C
682.00
4840.00
665.00
4900.00
675.CC
SCO0.0C
4770.00
664.00
*68Q0.B
646.00
5200.00
631.CC
5400.00
SIo0.uU
682.00
5120.00
658.00
5290.00
636.CC
5960.00C
5400.0O
614.00
5520.00
623.00
5610.00
626.C00 5790.00
*08G.UU
674.00
61W0.0C
670.00
SlL # bARuNCCOVEP-CER.GRqCV
C8k
EASY
NCMRAL
CIFFICULT
S100.00
6.jU
C.0
0.0
U.0
Bolivian Base Scenario Data
Figure 30
161
6LTV.
893.00
891.~'0
849.00
864.00
823.00
802.00
765.03
719.03
704.00
714.00
7CO.C0
69C.00
666.00
60C.00
67C.00
PNT
SUR
0.0
ORAINAGE RELATEC CATA-CRAIN
IPPASS
IVERAIN
MATR-BLOE
,.00
1.00
40.00
HAUL GISTANCESCCKSTRUCTION
PT-RAIN
1.00
g-8UR
HAULDIST
LAYER1
LAYER2
10.UO
1.00
2.00
0.0
CUNbTRUCTIAu PROCUCTIVITIES + COSTS-PROD
SITE PRkPAKATICN
EASY
NCOPAL
4ARC
LCOST
O.u
0.0
0C.1.
127.20
ARIThw RK
BOAROG
TRANSPORT
P'OC
LCCST
0.0
0.0
825.00
1057.00
PAVEMENT
FRGu
SOURCE
TRANSPORT
ICOST
j48.U0
0.0
0.0
495.70
0.0
0.0
0.0
0.0
k0.
C.C
0.0
0.0
495.70
0.0
0.0
348.00
DRAINAGt
5.00
PO. . CULVERTS .
SCUST
WEIG-T
TCOST
384.uU
55.00
0.02
52j.#.
110.CO
0.02
71..Uu
16C.C0
0.02
AUG5.uJ
210.C3
0.02
1486.,0
290.00
C.02
OThtR L.MPJNENTS
SJ(I.z
2LAeCR
1TC'ST
ILABCk
U.u
0.0
0.0
0.0
MAINTENANIo COSTS ANC PRCCUCTIVITI ES-MUC
81T1b
OUR FTRK
TqALCR
7CT:RGD
".
'.00
86.00 .
9
154.uu
OLAb.jb
EQCCER
FCREAPn
TCRIVER
6.uu
8.00
13.40
6.00
0IE~ELFULL GRCCST
GCCOST
wI'ERC
0.0
T.0
3.!
0.0
USeR LoST.tCON. AND 4ARKET- ECCKCMARK
LAb.~A
DRIVER
GCSCCST
DIESEL
b.1J
6.00
0.0
0.0
6.40
6.CO
3.0
0.0
TIRE CCT
IhlTIAL COST
MARKET
ECONTC
MARKET
LCCNJM
3bUo.UJ. 54000.00
313.00
468.00
39
5760C.00
351.30
576.00
93oto.UJ 1400.CU
4
1440.10
2052.00
VEHICLE JATA- VEF
WTCQWLS HRSEPWR
UcWEILLL
VE1.T
u.LUE 01 .. 84E 03 0.45E 03 0.410
02
u.2ýt Oi
u.27E C4 T.16E C4 0.14E 03
u.30F Uo 0.31E 04 0.23E T4 0.11E 03
0b.k%
FLT-MEC
0.0
FLT-LOT
C.C
PAVEMENT
LAYER3
SHCLLDER
0.C
2.CO
MAIkTEhANCE
GRAVEL
2.CC
WATER
0.0
PATC)0.0
CLLVERTS
200.00
EOCOST
854.40
ECCOST
7464.CC
EQCCST
3446.4C
0.0
O.0
3446.4C
RCLLER
77.5C
LIQAS-P
0.0
TRACTOR
75.CC
PAT7IX
C.0
VEHICLE
ECONCIP
MARKET
9.7C
11.20
5.0c
5.40
26.10
26.00
DSNSPEEC
0.12E 03
0.45E 02
0.94E 02
162
WTRTRK
71.0C
CJVSEAL
0.0
CARGO COST
MAk, E
0.0
0.0
7.0
0.0
0.0
0.0
EC3NCM
CHPVEHH
0.10E 0!
0.119 01
).10E r1
VEHWCTF
01
J.20E Cl
0.24E 01
0.17E
VEHHT
AIRPCEFP
0.18E 01 C.17E-01
0.19E Cl C.24E-01
C.340-01
0.250 Cl
FUELTYPF
0.0
.C
~.n
Appendix D
The Earthwork Models
Earthwork costs are often the largest single construction cost component in low volume roads and they
are often the hardest to estimate.
A wide variety of earthwork estimating techniques
exist and considerable development has gone into computer
aided roadway design systems.
These systems are of
high accuracy but require large amounts of input data.
This is
in contrast to the requirements of the HCM
which can accept
less accuracy so long as the input
requirements are also reduced.
The earthwork models used in the HCM require as
input the template and cross section of the pavement
and either a series of stations taken along the centerline of the roadway or
contour line densities which
represent the rise and fall of the roadway.
The one point model uses as input the series of
stations of both the roadway and terrain alignment taken
along the center-line of the road.
It computes earth-
work quantities taking into account pavement design and
the horizontal template of the roadway using the average
end area approach.
In this case the end areas at a
1.6 3
terrain station are determined by summing the trapezoidal
sections
across the roadway.
Suitable consideration
is given to problems caused by transitions from cut
to fill
and the need to maintain grades.
The contour line crossing density model was derived
from work performed by Augusto Soux (52).
This model
estimates the earthwork volume required to bring a roadway
alignment to grade as a function of the maximum allowable
grade, road width, side slope, and the density of ten
foot contours per mile.
The data base was generated using a simple one
point terrain model and utilized 84 separate roadway
designs through a wide spectrum of terrain types.
Road
profiles were fitted to these terrain profiles and adjusted
by trial and error to yield a minimum earthwork design,
while at the same time retain a balance between cut and
fill.
The earthwork volumes were then plotted against
contour density and curves were fitted to these data
points with one for each maximum grade.
The subroutine
RFETH uses one set of the data developed and while it
is properly sensitive to variations in design and topography the current version should be used with care.as
limitations in the data base and the orientation of Souxls
study to high design standard roads may cause some
problems in transferring the results to low standard
roads.
(The material in this appendix appeared in a different
form in
Working Paper 96 of the International Bank for
Reconstruction and Development
It was prepared by
Economics Department.
Messrs. Moavenzadeh, Stafford, Suhrbier,
and Alexander of CLM Systems, Inc. ( Consultants,
Cambridge, Mass.) ( 64).).
1b5
Appendix E
Listing of the Highway Cost Model
The remainder of this appendix contains a
listing of
CONSTR.
the routines MAIN, NETWRK, STRAT, SAVDAT, and
These five routines
make the cost estimating
routines of the HCM a more effective and readily used
tool for planners than it was initially.
166
C
C
MAIN PROGRAM OF THE HIGHWAY COST MODEL
THIS SET OF COMPUTER PROGRAMS WAS DESIGNED AND
UNDER DCT CONTRACT 05-00096
PROGRAMMED AT MIT
INTEGER OU,OYRMOD,OTRACE,TPMF ,OSWTH(3)
SUMD(12),OUTPT(12), TOT AL(12),
DIMENSION SUM(12),
FOREX(7),
OUTFR(28), DOLAR(2),
,GROW(7),
1 OUTPD(12)
1
C
12
13
HCM
HCM
HCM
HCM
HCM
10
20
22
25
30
HCM
40)
HCM
HCM
HCM
,TPMF,DISC,PNTPMF,IOIND
COMMON/INOUT/IN,OU ,IRCON,OYRMOD,OTRACE
HCM
1 , I ODVD
HCM
COfMMON/POLICY/ POL (30,20),COST(5,20) ,SAVE(20,170),RSTRT(30,4),
HCM
CONCOS(30,4),
1 NODE(30,3),NRECON,NNODE,NSTRT,DLSIGN(27,12),
HCM
2 STRMPL(20,6)
HCM
,TGROWS,GROW,SUM,SUM,TOTAL,TASK ( 1 2)HCM
COMMON/RMBR/ BCCS(7),ECOS(7)
HCM
1, GTTL,GTTLD,5STCST,CSTRT,OUTPT,OUTPO
HCM
14CM
COMMON STOR(963)
HCM
HCM
STOR(961) )
EQUIVALENCE (OSWTH(1),
HCM
IN=5
HCM
OU=6
HCM
,
IODVD
REAO(IN,12) OSWTH,OYRMOD,OTRACE,TGROWS,TPMF,MORE
HCM
IF ( TPMF.EQ.O) TPMF=1
HCM
IF( OYRMOD.EQ.0) OYRMOD=1
HCM
WRITE(OU,13) OSWTH,OYRMOD,OTRACE,TGROWS,TPMF
HCM
CHECK OUTPUT FORM ( PER K CR TOTAL ROAD )
HCM
IF( IODVD. NE.0)WRITE(OU, 14)
HCM
CALL PMIN
HCM.
CALL STRAT
HCM
CALL ERASE( CONCOS,120)
HCM
CALL NETWRK
HCM
IF(MORE.NE.0) GO TO 1
HCM
CALL EXIT
HCM
)
FORMAT( 512,815
HCM
CONSTRUCTION',13,'
FORMAT('1 OUTPUT SWITCHES FOR THIS RUN ARE
FMONY(3)
I
50
60
70
80
83
86
87
90
100
110
120
130
140
150
160
170
180
100
200
210
220
230
240
250
260
270
280
290
300
310
14
00
1 MAINTENANCE',I3,'
USER',13/'
OUTPUT IS PRINTED FOR YEARS THATHCM
2 ARE A MULTIPLE OF',I3,'
UNLESS THIS NUMBER',I3,'
IS POSITIVE'/ HCM
3' THE TRAFFIC GROWTH SWITCH IS',T4,' AND THERE ARE',13,' SFTS OF HCM
4 INITIAL TRAFFIC CONDITIONS ASSOCIATED WITH THIS PROJECT ' )
HCM
FORMAT('0
***,,*
ALL COSTS ARE FOR THE TOTAL LENGTH OF THE ROHCM
iAD SECTION IN QUESTION
*****
'/'
-********PLEASE DISREGARD " PERHCM
2 KILOMETER " IN OUTPUT HEADINGS
HCM
END
HCM
320
330
340
350
360
370
380
390
C
C
71
SUBROUTINE NETWRK
NET
THIS PROGRAM CAUSES THE DECISION NETWORK TO BE STEPPED THRO UGH AS NET
NET
INTEGER OU, OYRMOD,'OTRACE,TGROWS
,ONVEH,OSWTH(3),RBLD( 11) ,TPMF, NET
1 RECON(25), STRT,YR,YR F,CCNST,YRICNT
NET
REAL INT, MAPrL(20.),
HOTST(10), MARK(32)
NET
DIMENSION ALIGN(3),PROF(104) ,TEMPL(15),PAVE(1 2) ,ROUGH( 13),
NET
1IEMAN(7,3),TRAF(7),ECO N(4),TOPOG(305),GOLGY(3) ,GRDCV(4),
NET
2DRAIN(8 ),PROD(54), ECON 0(32),VEH(7,12) ,UT(150)
,WORK(40) ,
NET
3UXYZ(25)
NET
DIMENSION
TRAFF(7,3), I OSWT( 3),SAVMPL(20)
NET
NFT
COMMON/INOUT/IN,0OU ,IR CON,CYRMOD,OTRACE ,TPMF, DISC,PNTPMF, I OIND
NET
1, IODVD
NET
COMMitON/POLICY/
POL (30, 20),COST(5,20),SAVE(20,170),RSTRT(30, 4),
NET
1 NODE(30,3),NRECON,NNO DE,NSTRT, CESIGN(27,12), CONCOS(30,4),
NET
2 STPMPL(20,6)
NFT
COMMON/RATEX/ FOREX 7) ,FMCNY(3),XRATE,
OUTFR(2 8) ,OUTFRS(28
NET
N
COMMON/R;MiBR/
BCOS(7
,ECOS(7), TGROWS,GROW(7),S UM(12),SUMD(1 2) ,
NET
1 TOT.AL(12),TASK(12)
GTTL,GTTLD,STCST(30,8),CS TRT(30,8) ,OUT PT(12),NET
2 OUTPD(12)
NET
COMMON/PMBR2/ TRAFF2(7 ,3)
NE T
NET
COMMON ALIGN,PROF,TEMPL,PAVE,ROUGH,OEMANTRAF,NPER,ECCN,MAPOL,
NET
1RBLD,TOPOG,GOLGYCBR,GRDCV,DRAIN,HDIST,PRODUXYZ,ECONO,MARK,NUVEH, NET
2 VEH,OUT,WORK ,CSITH
NET
NET
EQUIVAL. ENCE (TRAFF( 1, ), DEMAN(1,11))
,(YRFNPER),(INTECON(1)),
NE T
Sf( OU,IPRNT )
NET
DATA ICHBOD/5/
NET.
NET
AT FIRST ENTRANCE INTO NETWRK STORE USER SPECIFIED MAINTENANCE
NET
POLICIES IN SAVMPL
NET
DO 71 IK=1,20
NET
SAVMPL(IK)= MAPOL(IK)
NET
WRITE(OU, 2018)
NET
10
20
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
270
280
200
300
310.
.320
330
340
350
360
370
380
C
C
2012
IF(TPMF.EQ.1) GO TO 2001
NTPMF IS THE NTH SET OF INITIAL TRAFFIC CONDITIONS HAVING AN
ASSOCIATED PROBABILITY CF
CCCURRENCE
PNTPMF
NTPMF= TPMF
CALL ERASE( STCST,240)
STATEMENT 2012 IS THE STARTING POINT OF THE LOOP ASSOCIATED WITH
UNCERTAINTY IN PREDICTIONS OF INITIAL TRAFFIC
READ(IN,2013) PNTPMF
WRITE(OU,2014) PNTPMF
C
2001
C
C
C
C
C
CONTINUE
YR1CNT IS USED TO PERMIT THE USEP TO SUPPLY EMAND CURVES ONCE
YR1CNT=-1
NNODE IS THE 4 OF NODES IN THE DECISION NETWORK
NRECON IS THE # OF RECONSTRUCTIONS
NSTRT IS THE # OF STAGING STRATEGIES
STRT IS THE STRATEGY BEING EXAMINED
SC
START
"C
0
INITIALIZATION
OF VARIABLES
CS=0.
STRT=1
YR= 1
CONST IS A POINTER TO THE CONSTRUCTION ACTIVITY .BEING PERFORMED
THE ARRAY POINTED AT IS RSTRT
CONST =0
TOSWT(2)= OSWTH(2)
IOSWT(3)= OSWTH(3)
WORK(33) =0.
WORK(35)=0.
WORK(37)=0*
INITIALIZATION CF ARRAYS
C
C
INITIAL IZATION OF ARRAYS
CALL ERASE ( TRAF,7,SUM,12,SUMD,12,0UTPT,12,0UTPD,12,
1 RECON,25)
END VARIABLE INITIALIZATION
TOTAL,12,
NET
NET
NET
NET
NET
NET
NET
NET
NFT
NET
NET
NET
NET
NET
NET
NET
NET
390
400
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
N'13T
560
NET
NFT
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
570
580500
600
610
620
630
640
650
660
670.
.680
690
700
710
720
730
740
C
931
DISC = 1./((1.+INT)**YR)
IF(OTRACE.GT.O) GO TO
931
WRITE ( IPRNT,105 ) YR,DISC ,STRT
CONTINUE
IOIND=1
C
S01
C
1
C
-L12
13
C
CHECK IF THIS RUN IS NOT SPECIFIED USING THE TREE STRUCTURE
IF((NSTRT.EQ.0).AND.(YR.EQ.1)) GO TO 901
GO TO I
IOP=O
ENTER ROUTINE CONSTR AT ENTRY SIMCON FOR SI MPLE CONSTRUCTION
CALL SINCCN(IOPI
GO TO 9C11
CONTINUE
IS THIS A NODE
DO 12 I= 1,NNODE
IF((NOD E(I,1).EQ.YR).AND.(NODE( I,2).EQ.STRT))
CONTINUE
GO TO 14
CONTINUE
I IS THE NODE #
GO TO 13
IJ=I
TYPE= 1
C
14
C
9
SAVE ROAD AND TRAFFIC PROPERTIES
CALL SAVDAT (STRT,YR, IJTYPE)
CONTINUE
IS THIS (STRATEGY,YEAR)
A RECONSTRUCTION PERIOD
DO 9 1 =1,NRECON
TRSI= RSTRT(I,1)+.01
IRS4= RSTRT(I,4)+.01
IF ((IRSI.EQ.YR).AND.(IRS4.EQ.STRT))
GO TO 10
CONTINUE
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NFT
NET
EFT
NET
NETNET
NET
NET
NET
NET
NET
NET
NET
NET
NET.
NET
NET
NET
NET
NET
NET
750
760
770
780
790
800
810
820
830
840
850
860
870
880
890
900
910
920
930
940
950
960
970
980
990
1000
1010
1020
1030
1040
1050
1060
1070
1080
1090
1100
C
C
10
C
C
44
C
C
C
C
7C
72
",
C
73
_Q
75
74
C
C
11
112
C
C
9011
C
GO TO 112
I IS THE # OF THE RECONSTRUCTION
CONST= CONST +1
CALL CONSTRUCTION COSTING ROUTINES
CALL
CONSTR(STRT,YR, I J,CCNST, ICHBOD)
SELECTION OF MAINTENANCE POLICY
TRANSFER USER SUPPLIED MNTPOL
K=IJ
IF( RSTPT(K,3).GE.O.1 ) GO TO 73
DO 72 IK=1,20
MAPOL(IK)= SAVMPL(IK)
GO TO 74
TRANSFER PROGRAM SUPPLIED MNTPOL
JKK= RSTRT(K,3) +.01
DO 75 IK=1,20
MAPOL(IK)= STRMPL(IK,JKK)
IF(YR.FQ.1) GO TO 112
INDICATE TO MAINT THAT CCNSTRUCTION HAS OCCURRED
RECCN(YR-1)= 1
CHECK IF PREVIOUS CONSTRUCTION WAS THE NULL ALTERNATIVE
IF((CONST.FQ.1).nR.(RSTRT(CCNST-1
2).GT.1. )) GO TO 112
DO 11 IZ=1,NUVEH
00 11 IT=1,3
TRAFF(IZ,IT)= TRAFF2(IZ,IT)
CONTINUE
CHECK IF THE NULL ALTERNARIVE IS BEING EXAMINED
IF(PSTRT(CO)NST,2).LE.1.1 ) GO TO 141
USE THIS SFCTIOON IF LINEAR STRATEGY SPECIFIED
CONTINUE
CALCULATIONS OF USER COSTS
CALL USER (YR,YR1CNT)
NET 1110
NET 1120
NET 1130
NET 1140
NET 1150
NET 1160
NET 1170
NET 1180
NET 1190
NET 1200
NET 1210
NET 1220
NET 1230
NET 1240
NET 1250
NET 1260
NFT 1270
NET 1280
NET 1290
NET 1300,
NET 1310
NET 1320
NET 1330
NET 1340
NET 1350
NET 1360
NET 1370
NET 1380
NET 1390
NET. 1400
NET 1410
NET 1420
NET 1430
NET 1440
NET 1450
NET 1460
C
1341
1344
C
HIF
1346
1345
1342
IF(YR.EQ.1) WRITE(OU,1029) YR,((TRAFF(IZIT),tl=1,w3),,OW(IZ),
1 IZ1,NUVEH )
CALCULATIONS OF MAINTENANCE
CALL MAINT(YR,RECON)
SUM MAINTENANCE AND OPERATING COSTS
CHECK ON FORM OF OUTPUT
DIVIS=ALI GN(1)
IF( IODVD. NE.0) CIVIS=1.
00 1341
I=5,8
OUTPT(I) SOUT ( I+71)/rIVI S
OUTPT(9) = OUT( 103)
OUTPT(10) =OUT( 102)
OUTPT( 11) =OUT( 1C4)
OUTPT ( 12) =OUT (101)
CHECK ON FORM OF OUTPUT
( IODV D.EQ.O) GO TO 1345
DO 1346 1 =9,12
OUTPT(I )= OUTPT ( I )* ALIGN( 1)
DO 1342
I=5,12
OUTPO (I )=OUTPT( I)*DfISC
SUM( I )=SUM(I)+ OUTPT(I)
SUMD( I)= SUMO(I)+ OUTPD(I)
TOTAL(5)= OUTPT(5)+ OUTPT(6)+ OUTPT(7)
TOTAL(6)= OUTPD(5)+ OUTPD(6)+ OUTPO(7)
TOTAL(7)= SUM(5)+ SIJM(6)+ SUM(7)
TOTAL(8)= SUMD(5)+ SUMD(6)+ SUMO(7)
TOTAL ( 11) =SUM(9 )SUM(10)(0
SUM(11)+SUM(12)
TOTAL(12)=SUMD(9)+SUMD(10)+SUMD(11) +SUMD(12)
TOTAL(9)=OUTPT(9)+OUTPT( 10 )+OUTPT(11)++UTPT(12)
TOTAL(10)=OUTPD(9)+OUTPD(10) +OUTPD( 11)+OUTPD(12) GTTL= TCTAL(3) + TOTAL(7) + TOTAL(11)
GTTLD= TOTAL(4) + TOTAL(8) + TOTAL(12)
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NE T
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
1470
1480
1490
1500
1510
1520
1530
1540
1550
1560
1570
1580
1590
1600
1610
1620
1630
1640
1650
1.660
1670
1680
1690
1700
1710
1720
1730
1740
1750
.1760
1770
1780
1790
1800
1810
1820
OTRACE.GT.0)) GO TO 504
IF ((YR.EQ.YRF).AND.(
IF(OTRACE.GT.O) GO TO
932
IF( IOIND.LT.
0.5) GO TO 932
NET
NET
NET
NET
NET
IF(OSWTH(2).LT.1) GO TO 1026
NET
IF(IODVD.EQ.0) GO TO 1027
NET
COMPUTE EFFORT REQUIRED FCR ENTIRE POADWAY
C
NET
DO 2019 IK=1,12
NET
2019
TASK(IK)= TASK(IK)*ALIGN(1)
NET
WRITE(IPRNT,1028) TASK
1027
NET
1026 CONTINUE
NET
NET
IF(OSWTH(3).LT.1) GO TO 504
NET
C
PRINT DETAILED USER OPERATING COST CATA
NET
505 WRITE(IPRNT,5002) (OUT(I),I=105,146),(TRAF( I),1=1, 7)
NET
NET
504
CONTINUE
WRITE(IPRNT,304 ) (OUTPT( I),CUTPO(I) ,SUM(I),SUMO(I) ,OUTPT(I+4) ,UTP 'NET
ý,OUTPT(12) ,OUTPD( 12),SUM(12) ,SUMD'NET
ID(I+4),SUM(I+4) ,SUMD(I+4),I=5,7)
NET
1(12), (TOTAL(LL ),LL=5,12 )
NET
5033 CONTINUE
NET
932
CONTINUE
NET
C
NET
FOREIGN COST FOR MAINTENANCE EQUIPMENT
C
NET
IF(ECON(2) .GT. 0.) GO TO 621
NET
OUTFR(17) =OUTPT(6)*FOREX(7)
NET
OUTFR(18)=OUTPD(6)*FOREX (7)
NET
OUTFR(1 9)=SUM(6 )*FOREX(7)
NET
OUTFR(20) =SUM0(6)*FOREX(7)
NET
C
NET
USED IN CPERATING MCDEL
C
FOREIGN CAPITAL
NET
WORK(33)=WORK(32) +WORK(33)
NFT
WORK(35)=WORK(34) +WORK(35)
NET
WORK(37)=WORK(36) +WORK(37)
NET
OUTFR(21)=WORK(32)FOREX( 1) +WORK(34)*FOREX(2)+WORK(36)*FOREX(3)
NET
OUTFR(22)=OUTFR(21 )*DISC
1830
1840
1850
1860
1870
1880
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
20202
2039
2040
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2160
2170
2180
C
333
OUTFR(23)=WORK(33)*FOREX(1)+WORK(35)*FOREX(2)+WORK(37)*FOREX(3)
OUTFR (24)=OUTFR(23)*DISC
TOTAL FOREIGN CAPITAL COSTS
OUTFR(25)=
OUTFR(17) +OUTFR(21)
OUTFR(26)
OUTFR(18) +OUTFR(22)
OUTFP(27) =OUTFR(15)+OUTFR(19)+OUTFR(23)
OUTFR(28)=OUTFR(16)+OUTFR( 2C)+OUTFR(24)
IF(YR.EC.1) GO TO 333
GO TO 334
OUTFR(25) = OUTFR(25) + OUTFR(15)
OUTFR(26)
334
= OUTFR(26)
+
CUTFR(16)
CONTINUE
COMPUTE COSTS IN DOLLARS
00 5034 I=17,28
5034
OUTFRS(I)= OUTFR (I)*XRATF
IF ((YR.EQ.YRF).AND.(
OTRACE.GT.0))
IF((OTRACE.GT.0).OR.(
IOIND.LT. 0.5))
H
-QC
PRINT OUT FOREIGN COSTS
Ln
5032 WRITE(IPRNT,600C) YR,FMONY
,(OUTFR(
621
IF((OTRACE.GT.O).OR.( IOIND.LT. 0.5))
C
933
C
141
,C
C
C
WRITE(IPRNT, 310)
CONTINUE
GO TO 5032
GO TO 933
I) ,I=17,28)
GO TO 933
GTTL, GTTLD
STEP TO NEXT TIME PERIOD
CONTINUE
YR= YR+1
CHECK FOR EN OF ANALYSIS
IF( YR.GT.YR
) GO TO 714
DISC = 1./(
+INT)**YR)
THIS SECTION LIMITS OUTPUT TO YEARS ZERO MODULO
MODK =
MOD(Y R,OYRMOD
IF(MODK.EQ.
OSWTH(2)= 0
0)
)
GO TO 704
INTM
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NFT
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NFT
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
2190
2200
2210
2220
2230
2240
2250
2251
2252
2253
2255
2257
2260
2270
2280
2290
2300
2310
2320
2330
2340
2350
2360
2370
2380
2390
2400
2410
2420
2430
2440
2450
2460
2470
2480
2490
704
706
934
OSWTH(3)= 0
IOIND =C
GO TO 706
OSWTH(2)= IOSWT (2)
OSWTH(3)= LOSWT(3)
IOIND=l
IF(OTRACE.LE.O) WRITE(OU,2018)
CONTINUE
IF((OTRACE.GT.0).OR.(
ICIND.LT. 0.5)) GO TO 934
WRITE ( IPRNT,lC5 ) YR,DISC ,STRT
CONTINUE
IF( NSTRT.EQ.0O)
GO TO 1
C
C
C
H 714
i-J
C
C
THIS STRATEGY HAS BEEN EXAMINED
STORE THE COSTS DUE TO THIS STRATEGY IN ARRAY CSTRT
CONTINUE
INDICATE TO USER AND CONSTR
THAT THE FIRST DEMAND CURVES HAVE
BEEN READ AND THAT USER SHOULD NOT READ ANOTHER SET
YR1CNT=YR CNT+2
YR=YR-1
WRITE(OU, 1029)
1 IZ=1,NUVEH )
CSTPT ( STRT,
CSTRT ( STRT,
CSTPT ( STRT,
CSTRT ( STRT,
CSTPT ( STRT,
CSTRT ( STRT,
CSTRT ( STRT,
CSTRT ( STRT,
C
GO TO 9011
YR,(TRAFF(IZ,1),r)UT(IZ+125),TRAFF(IZ,3),GROW(IZ),
1) =
2) =
3) =
4) =
5)=
6)=
7)=
8) =
TOTAL(
3)
TOTAL( 7)
TOTAL(
11)
GTTL
TOTAL(
4)
TOTAL( 8)
TOTAL( 12)
GTTLO
ZERO THE RECONSTRUCTION
CALL ERASE ( RECON,25)
ARRAY
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NFT
2500
2510
2520
2530
2540
2550
2560
2570
2580
2590
2600
2610
2620
2630
2640
2650
2660
2670
2680
2690
2700
2710
2720
2730.
2740
2750
2760
2770
2780
2790
2800
2810
2820
2830
2840
2850.
C
C
C
421
IOIND=1
ARE ANY NODES ON THIS STRATEGY UNEXAMINED
CONST= CONST+1
IF(CONST.GT.NRECON) GO TO 40
IF(NRECON.EQ.0) GO TO 40
YR= RSTRT(CCNST,1 )
Sl= RSTRT(CONST,4)
IS1= Sl+.01
DISC = I./((1.+INT)**YR)
WRITE(OU,1051) IS1,YRCISC
LOCATE THE NODE TO BE RESTORED
00 42 K=1,NNOQE
IF(NODE (K,2) .EQ. IS1)
42
423
GO TO 41
CONTINUE
IS1=IS1-I
GO TO 421
O
C
41
411
CONTINUE
Kl=K
IF(NODE(K1,1).EQ.YR) GO TO 441
Kl= KI+1
IF ( K1.GT.NNODE) GO TO 423
GO TO 411
C
441
C
C
CONTINUE
THE NODE # IS SET EQUAL TO Ki
IF(NODE(K1,2).NE. IS1 ) GO TO 443
TYPE=-1
COMPUTE EXPECTED COSTS DUE TO UNCERTAINTY
CALL SAVDAT(IS1,YR,K1,TYPE)
STRT= 51+.01
GO
443
TO 44
WRITE(rUt,201)
YR,S1
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
2860
2870
2880
2890
2895
2900
2910
29?0
2930
2940
NET
2050
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NET
NEFT
NET
NET
2960
2970
2980
2990
3000
3010
3020
3030
3040
3050
3060
3070
3080.
3090
3100
3110
3120
3130
3140
3150
3160
3170
3180
3190
3200
NET
NET
--~
NET
NET
( K, (POL(K1,K2),K2=1,16),CSTRT(KI,8),KI=1,NSTRT)
NET
NET
IF( TPMF.EQ.1) RETJRN
NET
NET
'
'
C
COMPUTE EXPECTED COSTS DUE TO UNCERTAINTY
IN TRAFFIC PROJECTIONS NET
DO 2016 Kl= l,NSTRT
NET
NET
DO 2016 K?= 1,8
NET
2C16
STCST(KI,K2) = STCST(K1,K2)+ PNTPMF*CSTRT(K1,K2)
NTPMF= NTPMF-1
NET
IF( NTPMF.GE.1) GO TO 2012
NET
WRITE ( CU2017)
NFT
NET
WRITE(OU,100) ( K,(STCST (K,J), J=1 ,8),K=1,NSTRT)
,KI=1,NSTRT)
,STCST(K1,8)
K1,(POL(KI,K2K2=1,16)
(
NET
WRITE(OU, 1771)
RETURN
NET
H
NFT
OD
C
FORMAT STATEMENTS
NET
100
FORVAT('O
COSTS FOR THIS RUN ARE '//
NET
1
T30,
' UNDISCOUNTED ',
NET
T75,'
DISCOUNTED ' /
A ' STRATEGY','
CONSTRUCTION
MAINTENANCE
OPERATING
TOTA L' I , NET
1 5X,
'CONSTRUCTION
MAINTENANCE
OPERATING
TOTA L' NET
B /R/
15, 8F14.0 ))
NET
105
FORMAT('0 YEAR',13,'
DISCOUNT FACTOR',F7.3,'
NET
STRATEGY', 13)
201
FORMAT('0 ERROR IN RECONSTRUCTION LIST, CANNOT FIND RECONSTRUCT IONNET
NFT
STRATEGY ',FIO.0)
I AT YEAR',IS,'
$/ NET
304 FORMAT(lHOT30,'MAINTENANCE COSTS ($/KM)',T80,'OPERATING COSTS
//T22,2 'T NET
IKM)'
NET
2HIS PERIOD',14X,'SUM TO OATE',8X)/T16,4('ACTUAL
DISCOUNTED
NET
3)/
S2.0/'
MATERIAL' ,T12 ,8F12.0 NET
EQUIPMENT',T12,8F
4' LABOR',T?2,8Fl2.0/'
TOTAL' ,T12,8F12.0) NET
5/' INCREMENTAL WILLINGNESS TO PAY',T60,4FI2.0/'
ACTUAL
DISC NET
FORMAT( 'OSUM OF ALL COSTS TO DATE($/KM)
310
NET
I0UNTED '/T33,2Fl5.0 )
40
RETURN
CONTINUE
IF( TPMF.GT.1)
WRITE(OU,1 00)(
WRITE(0U,1771)
ITE(OUr2015)
(CSTRT(KJ),J=1,8),K=1,NSTRT
PNTPMF
)
I
3210
3220
3230
3240
3250
3260
3270
3280
3290
3300
3310
3320
3330
3340
3350
3360
3370
3380
3390
3400
3410
3420
3430
3440.
3450
3460
3470
3480
3490
3500
3510
3520
3530
3540
3550
3560
1028
FORMAT( 'OPER KILOMETER MAINTENANCE COSTS BY TASK'/
I BLADE DRY
NET
1 REGRAVEL
ROADSIDE MOW DRAINAGE
BLD WET
PATCH CLDMIX HA NET
HAUL A GGRGT PTCH RUT
SEAL CRK
'/8F12.0 / '
2UL CLDMIX
HAUL R NET
3UTPTCH
SHOULDER '/ 7F12.0 )
NET
1029
FORMAT('0
TRAFFIC IN YEAR',15,' HAS THE FOLLOWING PROPERTIES
NET
' VEHICLES /DAY
BASE COST$/KM
FLASTICITY
GROWTH RATF'/
NET
2(T48, F5.0,3F15.3
))
NET
1051
FORMAT('1 START OF ANALYSIS FOR STRATEGY', I5,'
IT IS YEAR',14,'0 NET
I AND THE DISCOUNT FACTOR IS ',
F7.3)
NFT
1771
FOPMAT('O',
T40,'STRATEGIES AND CGSTS'/
NET
1 ' STRATEGY
DESCRIPTION' ,T0,'TOTAL DISCOUNTED COST'/
NET
2
(15,4(F5.0,2X,2A4,3X,F4.1),F 5 0
) )
NET
2013
FORMAT(8F10.2)
-
NET
FORMAT('1 THE ANALYST SPECIFIED PROBABILITY ASSOCIATED WITH THE
NET
I INITIAL TRAFFIC CONDITICNS IS',F10.4 / )
NET
2015
FORMAT('I THE USER SPECIFIED PROBABILITY ASSOCIATED WITH THESE
NET
1 COSTS IS', F10.4 /)
NET
I-2017
FOPMAT('1
THE EXPECTED COSTS OF ALL STRATEGIES ARE AS FOLLOWS') NET
`2018
FORMAT (1H1)
NET
5002 FORMAT(1HO,'
DETAILED OUTPUT FOR USER COST MODEL BROKEN DOWN BY VENET1HICLE TYPE PER VEHICLE KILCMETER'/
NET
A
' LABOR HOURS',19X,7F10.3/'
VELOCITY, KPH',17X,7F10.3/NET
2' FUEL CONSUMPTION, LITERS',6X,7FlO.3/f MARKET COST, DOLLARS',
NET
310X, 7F10.3/' PARTS COST FACTOR PER 1000 KM',1X, 7F10.3/' INC.WILLNET
4. TO PAY
',5X,
7F10.3/' NUMBER OF VEHICLES',T30,7F10.1)
NET
6000 FORMAT(//30X,
' FOREIGN EXCHANGE COSTS FOR YEAR ',1I2,'
IN ',3A4,NET
1 ' ARE'/
T31,'THIS PERIOD',T60,'SUM TO DATE'/T26,'ACTUAL',T41,
NET
NET
2'DISC',T56,'ACTUAL',T71,'OISC'/
3
'
MAINTENANCE TOTAL',T21,4FL5.1/' USER TOTAL',T21,4F15.1//NET
4' GRAND TOTAL',T21,4FI5.1)
NET
END
NET
2014
3570
3580
3590
3600
3610
3620
3630
3640
3650
3660
3670
3680
3690
3700
3710
3720
3730
3740
3750
3760
3770
3780
3790
3800
3810
3820
3830
3840
3850
3860
3870
C
SUBROUTINE STRAT
THIS RCUTINE READS THE RECONSTRUCTION STAGING DATA
INTEGER OU,OYRMOD,OTRACE,TGROWS
,DNVEH,OSWTH(3),RBLD(11)
TPMF
DIMENSION ALPHA(11,2)
DIMENSION RSTRT (30,4), NODE(30,3),POL(30,20),COST(5,20),
1 SAVE(20,170), DES.IGN(27,12)
COMMON/INOUT/IN,CU ,IRCON,OYRMOD,OTRACE
,TPMF, DISCPNTPMF, IO IND
COMMON/POLICY/
POL,COST,SAVE,RSTRT,NODE,NRECON,NNODE,NSTRT ,D ESIGN
I
1 ,
CONCCS(30,4)
COfYMON/YRCOST/YRCS (5)
EQUI VAt. ENCE
EQUIVALENCE
I PRNT, OU)
NSTRAT,NSTRT)
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STR.A
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
ST R A
NNODE=# OF NODES
NRECON IS THE # OF CONSTRUCTION PERIODS
NSTRT IS THENUMBER OF STAGING STRATEGIES
DATA Al PHA /'NUll
'.'FART'.'FART'.'rRAV'.~'GRA V','SURF,'LASPH'
STRA
1 'EART','GRAV',i'SJRF','ASPH '
'
','HIS ' ,'H2S ','ELS',' EL2S' , STRA
2 'ACES','ALTS','K2
','EL2 ','ACE ','ALT ' /
STPA
C
NALPH IS # OF ROAD DESIGNS
DATA
15
351
C
IN STORAGE
NALPH/12/
YRCS(1)=-l
READ(IN,15) NSTRAT,NEXDS,IDESSW
FORMAT(I110)
WPITE(OU,351) NSTRT,NEXDS
FORMAT('1 THE NUMBER OF RECONSTRUCTION STRAT EGIES
2E NUMBER OF COST SETS IS ',I5 )
NSTRT IS THE NUMBIER OF STAGING STRATEGIES
NRECCN = 0
IF
C
C
(NSTRAT.EO.0)
GO TO
199
INITIALIZE ARRAYS
CALL ERASE( RSTRT,120,POL,600,NODE,90
)
IS', 15,'
STRA
STRA
STRA
STRA
STRA
STRA
AND THSTRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
10
20
50
60
70
80
90
100
110
120
130
140
150
160
170
190
200
210
220
230
240
250
260
270
280
290
300
310
320
325
330
340
350
360
370
C
CHECK IF NEW DESIGN IS DESIRED
IF( IDESSW.EQ.O) GI0 TO 84
DO 82 IZ=1,IDESSW
READ(IN,15) ID
WRITE(OU,83) ID
READ (IN,80) AL PHA(ID,1
ALPHA( ID,2)
WRITE(OU,81) AL PHA(ID,1
ALPHA(IO1,2)
READ(IN,831)
( DESIGN(
ID),1I=1 11))
READ(IN,831)
( DESIGN(
ID),I=16,27)
WRITE(OU ,802)
WRITE(OU,830) ( DFSIGN(I,ID),I=1,11)
WRITE (OU,803)
WRITE(OU,830) ( DESIGN( I,ID),I=16,27)
CONTINUE
WRITE(OU,174 )
DO 175 I =1, NSTRAT
READ
(IN,176)
WRITE(OU,177)
175
178
180
(POL(IJ),J=1,16
(
)
POL(IJ),J=1,16
)
CONTINUE
N=O
IF( NEXDS.LE.0) GO TO 180
N=N+1
READ(IN,179) YRCS(N)
WRITE(OU,1792) YRCS(N)
READ(INi,179) ( COST(N,J),J=1,20
NEXDS= NEXDS-1
GO TO 178
CONTINUE
THIS SECTION TRANSLATES INPUT
THE REMAINING SUBROUTINES
NRECON=0O
N=NRECON
INITIALIZE COUNTERS
)
INTO A FORM THAT CAN BE USED BY
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STR A
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STR A
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
STRA
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
560
570
580
590
600
610.
620
630
640
650
660
670
680
690
700
710
720
730
150
151
C
C
C
C
C
155
C
C
C
C
1521
J=O
J=J+l
J4=-3
!F(J.GT.NSTRT) GO TO 190
J4=J4+4
-
!F(J4.GT.17) GO TO 150
TEST FOR DESIRED RECONSTRUCTION
IF( POL(J,J4).EQ.0) GO TO 151
FIND PROPERTIES OF THIS RECONSTRUCTION
INCREMENT RECONSTRUCTION COUNTER
NRECON= NRECON+l
N= NRECCN
YEAR
= PCL(J,J4)
RSTRT(N,1)
RECCNSTRUCTION TYPE
1=0
IF( I.G E.NALPH) GO TO 152
I=1 +1
GO TO 155
IF( POL (J,J4+2) .NE.ALPHA(1,2))
RSTRT(N ,2)
=1
MAINTENANCE POLICY
RSTRT(N,3)= POL(J,J4+3)
STRATEGY
RSTRT(N,4)= J
GO TO 151
ERROR IN INPUT DATA
WRITE(OU,153) J1
CALL EXIT
152
WPITE(OU, 153) J
CALL EXIT
C
190
WRITE ARRAY RSTRT ON PRINTER
WRITE(OU,191)
( I,(RSTRT(I,J),J=1,4),I=1,NRECON)
WRITE(OU,192)
STRA 740
STRA 750
STRA 760
STRA 770
STRA 780
STRA 790
STRA 800
STRA 810
STRA 820
STRA 830
STRA 840
STRA 850
STRA 860
STRA 870
STRA 880
STRA 890
STRA 900
STRA 910
STRA 920
STRA 930
STRA 932
STRA 936
STRA 940
STRA 950
STRA 960
STRA 970
STRA 980
STRA 990
STRA100O
STRA1010
STRA1020
STRA1030
STRA OLO4
STRA1050
STRA1060
STRA1070
C
C
C
C
C
THIS SECTION LOCATES NODES IN THE DECISION NETWORK
NODES ARE POINTS WHERE TWO OR MCRE ALTERNATIVES EXIST
I IS THE NODE NUMBER
THE SUBSCRIPT J REFERS TO STRATEGIES
IF ( NSTRAT.EQ,O) GO TO 199
NODYR1=-1
197
C
115
C
I=0
J=1.
J4=-3
J=J+l
IF ( J.GT.NSTRAT ) G 0 TO 194
LOCATE BRANCHES
J4=J4+4
IF ( POL(J,J4).EQ.0) GO TO 195
LABFL NCDES
I=1+1
INiOIJ
196
191
198
C
203
205
I
L
=
ruLIJ, J+
IF ( NODE(I,1).FQ.1 ) GO TO 207
LOCATE MAIN BRANCH
J1=J
J1=J1-1
IF(JI.EO.0) GO TO 1521
J14=J4
J14= J14-4
IF (J14.LT.1) GO TO 196
GO TO 1981
IF(POL(Jl,J14).EQ.O.)
NODE (1,2)=Jl
NODE(I,3)= NODE(I,3)+1
CHECK IF THIS NODE HAS BEEN PREVIOUSLY IDENTIFIED
11= I-1
IF(II.EC.0) GO TO 197
IF( NODE(I,1).EQ.NODE(II,1)) GO TO 205
GO TO 197
IF( NODE(I,2).EQ.NODE(I1,2)) GO TO 204
GO TO 197
STRA1080
STRA1090
STRA1100
STRA1110
STRA1120
STRA1139
STRAl149
STRA 150
STRA1160
STRAI170
STRA1180
STRA119O
STRAI200
STRA1210
STRAI220
STRA1230
STR41240
S'TRA 1250
STRA1260
STRA1270
STRA1280
STRA 290
STRA1300
STRA1310
STRA1323
STRA1330
STRA1340
STRA1350
STRA1360
STRA1370
STRA1380
STRA1390
STRA1400
STRA1410
STRA1420
STRA1430
C
204
C
C
207
C
C
C
209
208
C
C
C
C
194
UPDATE NUMBER OF BRANCHES FROM NODES I , I-1I
NODE(I,3)= NODE(T,3)-1
NODE(11,3)= NODE(Il13) +1
RESET NCDE COUNTER
1=11
GO TO 197
THIS SECTION IS USFD WHEN A STRATEGY IS SPECIFIED
CONTINUF
IF (NODYR1.LT.O) GO TO 209
A BRANCH FROM YEAR 1 HAS BEEN FOUND PREVIOUSLY
NODE(KNOYR1,3)= NODE( KNOYRI,3) +1
DECREASE NODE CCUNTER
1=I-1I
GO TO 197
THIS IS FOR FIRST BRANCH FRCM YEAR 1
KI=J
KI=Kl-1
IF(POL(Ki,1).EQ.O ) GO TO 208
NODE(I,2)= KI
NODE(T,3)=NODE( 1,3)+1
KNf]YRI =I
NODYR1=1
GO TO 197
WRITE OUTPUT
IN YEAR
DATA
NNODE IS THE NUMB ER OF NODES IN THE DECISION NETWORK
NNODE=I
WPITE(OU,200) I,( (NODE(J K),K=1,3),J=l, I)
202
RFTURN
199 WRITE(OU,193)
RETURN
C
FORMAT STATEMENTS
C
FORMAT(2A4)
8C
STRA1440
STRA1450
STRA1460
STRA1470
STRA1480
STRA1490
STRA1500
STRA1510
STRAI520
STRA1530
STRA1540
STRA1550
STRA1560
STRA1570
STRA1580
STRA1590
STRA1600
STR A 1610
STRA1620
STRA1630
STRA1640
STRA1650
STRA1660
STRA1670
STRA1680
STRA1690
STRA1700
STRA1710
STRA1720
STRA1730
STRA1740
STRA1750
STRA1760
STRA1770
STRA1780
STRA17O0
IT HAS THE FOLLOSTRA1800
FORMAT('
THE USER SPECIFIED DESIGN IS ',2A4 / '
STRA1810
IWING CHARACTERISTICS ' )
83
FORMAT (' DATA FOR USER SPECIFIED DESIG N #',15)
STRA1820
153
FORMAT('
RECONSTRUCTION STRATEGY ', 14 ,
IS IMPROPERLY SPECIFIED'STRA8I30
STRA1840
1 )
174
FORMAT( 'ORFCONSTRUCTION STRATEGIES ')
STRA1850
5(F2.0,2A4,2X,F3.0 ))
STRA1860
176
FORMAT(
F5.C0,2X,2A4,3X,F4.1 ))
177
FOPMAT (' t,5(
STRA1870
179
FORMAT( (5F10.2 ))
STRA 1880
191
FORMAT( '0 RECONSTRUCTION STRATFGIFS'/'
YEAR
TYPE STRA1890
STRATEGY ' )
STRAl900
1 MAINT. POLICY
))
STRA1910
1~2
FORMAT( (18,2FlO.O,FIO.4,FL0IO
t
193
FORMAT( '0 NJ RECONSTRUCTION THIS RUN E )
STRAl920
200
FORMAT( 'ONUMBER OF NODES IS ',13 /('
STRATEGY BRANCHES')/ STRA1930
YE AR
STRA194O
1
(( 14,19, 19,3X )))
802 FORMAT('
WIDTH
SLOPE
SHLD-WD
SHLD-SL
DTH-WD
DTHSTRA1950
FILL-SL
PAVE-WD
SIDE-CL') STRA1960
1-SL
DTH-WD
OTH-SL
CUT-SL
MAT-TPE
THI STRA1970
LAYERS
MAT-TPE
THICKNESS
0)3 FUt' R
I %
-•V
-,L)V
STRA19PO
THICK2
THICK3')
SHLD-TPE
THICKI
THICK
MAT-TPE
ICK
STRA190Q
830 FORMAT(12FI0.2)
STRA2000
FORMAT(8F10.2)
831
FORMAT('O THESE COSTS ARE FOR YEAR',F10.0)
1792
STRA2010
END
STRA2020
81
C
C
C
SAV
SUBROUTINE SAVDAT (STRT,YR,IJ,TYPE)
THIS PROGRAM STORES AND RESTORES ROAD AND TRAFFI CONDITIONS AT NODSAV
INTEGER STRT,YROUT
SAV
DIMENSION RSTRT (30,4), NODE(30,3),POL(30,?O),COST(5,20),
SAV
1 SAVE(20,170), DESIGN(27,12)
SAV
COMMON/POLICY/ POL,COST,SAVE,RSTRT,NCDE,NRECON,NNODE,NSTRT,DESIGN SAV
10
20
30
40
50
60
1
SAV
70
SAV
SAV
SAV
SAV
SAV
80
90
100
110
120
SAV
130
SAV
SAV
SAV
SAV
S-AV
SAV
SAVSAV
SAV
SAV
SAV
SAV
SAV
SAV
SAV
SAV
SAV.
SAV
SAV
SAV
SAV
SAV
SAV
140
150
160
170
180
190
200
210
220
230
240
250
260
270
280
290
300
310
320
330
340
350
360
,
IF
C
C
I
11
HC
10
C
9
C
C
3
111
101
92
2
C
CONCOS(30,4)
COMMON STOR(963)
COMMON/PMPBR/STOR2 (58)
COMMON/INOUT/ IN,OUT
IF TYPE IS NEGATIVE THIS IS A RESTORE
IF TYPE IS POSITIVE THIS IS A SA':E
(TYPE
) 1,2,3
RESTORE ROAD CONDITIONS
PAVFMENT TEMPLATE AND TRAFFIC LEVELS
DO 11 I=1,67
STOR(107+I)= SAVE(IJ,I)
PRODUCTIVITY
00 10 I=68,107
STOR(920+I-67)= SAVE(IJvI)
TRAFFIC DEMAND AND ELASTICITY
DO 9 1= 108,165
STOR2(I-107)= SAVE(IJrI)
WRITE(CUT,12) STRT,YR,IJ
RETURN
SAVE ROAD CONDTIONS
DO 111 I=1,67
SAVE(IJ,I)= STOR(107+I)
DO 101 1=68,107
SAVE(IJ,I)= STOR
(920+1-67 )
DO 92 I=108,165
SAVE( IJ, I)= STOR2 (1-107)
WRITE(OUT,31) STRT,YR,t IJ
RETURN
-
C
12
31
FORMAT STATEMENTS
FORMAT('O ROAD AND TRAFFIC CONDTICNS
I' STRATEGY ',13,'
YEARP',3,'
NODE
FORMAT('OROAO AND TRAFFIC CCNDITIONS
1' STRATEGY ',13,'
YEAR',I3,'
NODE
END
HAVE BEEN RESTORED',
NUMBER ',t3 )
HAVE BEFEN SAVED 'I
NUMBER ',13 )
SAV
SAV
SAV
SAV
SAV
SAV
370
380
390
400
410
420
CON
CON
CON
.CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
COMMON/ INOUT/IN,nu , IRCON,OYRMOD,OTRACE ,TPMF,DISC,PNTPMF,IOIND
CON
CON
I ,IOVD
COMMOF)N/ POLICY/ POL(30,201),CCST(5,20),SAVE(20,170),RSTRT(30,4),
CON
1 NODE(3 0,3),NRECON,NNODE,NSTRT,CESIGN(27,12),
CONCOS(30,4),
CON
CON
2 STPMPL (20,6)
COMMON/ RATEX/ FOREX(7),FMONY(3),XRATE,
CON
OUTFR(28) ,OUTFRS(28)
COMMON/ FMBRP/
CON
BCOS(7),ECOS(7), TGROWS,GROW(7),SUM(12),SUMD(12),
1 TOTAL( 12),TASK(12), GTTL,GTTLD,STCST(30,8),CSTRT(30,8),OUTPT(12),C ON
CON
2 OUTPD( 12)
C O,"'PCN/ YRCOST/YRCS(5)
CON
CON
COMMON ALI GN, PROF, TFMPL, PAVE,ROUGH, DEMAN, TRAF, NPER, ECCN, MAPOL,
CON
RBLD,TO POG, GOLGY, CBR, GRDCV, DRA IN, HD)IST, PROD,UXYZ, ECONO, MARK, NUVEH, CON
CON
VEH, OUTWORK ,OSWTH
CON
EOUIVA LENCE ( OU,IPRNT )
CON
DATA IN SUB/12/
CON
DATA TCPO, IOPI / 7,7 /
CON
K=CCNST
CON
CON
IJ=K
CON
WRITE(OU,1) K,( -RSTRT(K,J),J=1,4 )
CONSTR(STRT,YR, IJ,CONST,YRlCNT)
SUBROUTINE
THIS ROUTINE CAUSES THE CCNSTRUCTIGON AND RECONSTRUCTION (WHEN
IT THEN COMPUTES THE ACCRUED COSTS
DESIRED ) OF A ROAD.
PRINTS THESE COSTS AND THEN RETURNS CONTROL TO ROUTINE NFTWRK OR
ROUTINE DETER.
THE E NTRY POINT SIMCON IS USED FOR 'SIMPLE'
CONSTRU CTION.
IT IS THIS POINT THAT IS CALLED BY DET ER WHEN
RESURFA CING OF AN ASP HALT CP SURFACE TREATED ROAD IS REQUIRED
,TPMF',
INTEGFR OU, OYR MOD, OTR ACE,TGROWS
,rNVEH,OSWTH(3),RBLD(11)
1 RECCN( 25), STRT,YR,Y RF,CONST,YR1CNT
REAL IN T, MAPOL(20),
HDIST(IO), MARK(32)
DIMENS ION ALIGN(3),P ROF( 104),TEMPL (15) ,PAVE (12) ,ROUGH(13)
1DEMAN(7 ,3),TRAF(7),EC ON(4),TOPOrG(305),GOLGY(3),GRDCV(4) ,
2nRAIN(8 ), PPOD(54), ECO NO(32),VEH(7,12),0UT(150) ,WORK(40),
3UXYZ(25
C
H-
(O0
16
10
20
30
40
50
60
70
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
270
280
290
300
310
320
330
340
350
360
370
380
1
FORMAT ('0 CONSTRUCTION
#
1 STRATEGY '/ T20,15,2( 2F10.0-,FIO.0
YEAR
TYPE
MAINTPOL
CON
CON
CON
JO= RSTRT(IJ,2)
.CON
IOP=O
CON
IF( JQ.GT.IOPO
IOP=1
CON
IF( JQ.GT.IOP1
IOP=2
CON
CON
CHECK IF THIS IS NEW OR PAVEMENT CONSTRUCTION
C
CON
IF((IOP.EQ.O).OR.(IOP.EQ.1)) GO TO 17
CON
C
CHFCK IF THE ROAD WIDTH IS UNCHANGED. IF IT IS THIS IS A
CON
CON
C
TYPE 1 ( PAVEMENT ONLY) RECCNSTRUCTION
IF( TEMPL (1). EQ.0ES IGN( 1,JQ))
1)
Or=
CON
CON
C
ESTABL ISH DESIGN PARAMETERS
CON
CON
17
DO 10 I=1,15
10
TEMPL( I)= DESIGN(I,JQ )
CON
CON
TEMPL ( 12)= TEMPL(1)*2.
TE MPL ( 13)= TEMPL(11)
CON
CON
DO 101 1 I=1,12
CON
1011
PAVE( I)= DESIGN(I+15,JQ )
CON
C
CONVERT LAYER THICKNESSES TO.METERS
CON
C
CON
DO 1012 KL=4,12,2
1012
PAVE(KL)= PAVE(KL)/100.
CON
CON
PAVE(11)=PAVE( 1l.)/100.
CON
C
IF( OTRACE.GT.0O) GO TO 939
CON
WRITE(OU,78)
CON
78
FORMAT('
THE PAVEMFNT DESIGN FOR THIS CONSTRUCTION IS' )
CON
CON
WRITE(OU ,802)
802 FOPMAT('
WICTH
SLOPE
SHLD-W D
SHLD-SL
DTH-WD
DTHCON
FI LL-SL
PAVE-W D
DTH-SL
CUT-SL
1-SL
DTH-WD
SIDE-CL') CON
WRITE(OU ,830) (TEMPL(I),T=1,10), TEMPIL(12), TEMPL(1 3)
CON
CON
P30 FORMAT(12F10.2)
CON
WRITE (OU, 803-)
))
390
400
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
560
570
580
590
600
610
620
630
640
650
660
670
680
690
700
710
720
730
740
THICON
LAYERS
MAT-TPE
THICKNESS
MAT-TPE
803 FORMAT('
PAVE-CD
SHLD-TPE
THICK
THICKI
ICK
MAT-TPE
THICK2
CON
THICK3')
WRITE(OU,830) PAVE
CON
.CON
CONTINUE
939
CON
CON
CHECK FOR NEW ALIGNMENT
C
CON
IF (( IOP.NE.0). OR. ( YR.EQ.1)) GO TO 19
CON
READ NEW TERRAIN AND TOPOGRAPHICAL CATA
C
CON
ISTORE= IN
CON
WRITE(OU, 192)
CON
FOPRMAT('0
NEW ALIGNMENT CATA * )
192
CON
CALL PMINI (INSUB)
CON
CALL PMIN2 .(INSUB)
CON
IN= ISTORE
CON
19
CONTINUE
CON
IF( YRCS(1).LT.0) GO TO 92
CON
00 9 II=1,5
CON
IF (YR.GE.YRCS(II)) GO TO 91
CON
09
CONTINUE
CON
GO TO 92
CCN
91
JK=II
CON
00 11 1=1,20
CON
11
PROD(10+1)= COST(JK,I)
CnN
92
CONTINUE
CON
IF ( OTRACE.GT.0 ) GO TO 931
CON
WRITE(OU ,818) (PROD(I), I=11,30)
CON
PAVEMENT UNIT COSTS AND PRODUCTIVITIES
818
FORMAT('O0
I
'
PROD
SOURCE
TRANSPORT
LCOST
EQCOST
'/
CON
CON
2( 5F10.2,30X )
CON
931
CONTINUE
CON
C
CON
74
CONIND=1.
CON
GO TO 76
CON
CON
CALL CONSTRUCTION COSTING ROUTINES
CON
750
760
770
780
790
800
810
820
830
840
850
860
870
880
890
900
910
1920
930
940
950
960
970
980
990
1000
1010
1020
1030
1040
1050
1060
1070
1080
1090
1100
ENTRY SIMCON(IOP)
CONIND=-1.
C
76
C
C
C
C
CALL HWYCT(IOP)
CALL INITL TO INITIALIZE SURFACE PARAMETERS
CALL
C
H
H
INITL
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
),I=15,35),0UT(37),
CON
CON
8CR COST
BOR CON
SUM COSTS AND PRINT OUTPUT IF DESTRED
IF ( OTRACE.GT.2) GO TO 657
IF( OSWTH(1).LT.1 ) GO TO 657
PRINT DETAILED CONSTRUCTICN COST DATA
C
WRITE(OU,400) ( OUT(I),I=1,14),OUT(36),
(OUT(I
1 OUT(59),( OUT(I),I=38,5e),(OUT(I),I=60,72 )
CUT.VOL
FILL VOL
400 FORMAT(lHO,T16,'AREA
TOTAL'/T14,'
LABOR
EQUIPMENT
TIME
lHAUL
HOURSHECTARESCON
CON
2
CU.M
CU. M
,F12.0,T69,4Fl2.0/'
CON
SITE PRFP.',T9
3
$
$' /'
$
CON
T21,8FI2.0 / 'OPAVEMENT ' ,
4EARTHWORK',
MATL.COST
HAUL CON
T17,'AREA
VOLUME
A
TOTAL'/TCON
EQUIP.
LAYERCOST
LABOR
ICOST
TIME
$CON
HOURS
$
$
CU.M
216,'SQ.M
CON
$
$'/ T9,FI2.0,T107,F12.0 /
$
3
1
' LAYER 1',T21,7Fl2.0/' LAYER 2',T21,7FI2.0/' LAYER 3',T21,CON
17F12.0 /' SHOULDER',F11.0,T107, F2.0/' LAYER 1',T21,7FI2.0/' LAYERCON
LFNGTH OCON
2 2',T21,7FI2.0/' LAYER 3',T21,7FI2.0 /' DRAINAGE
TOTAL'/ T10,8F12.0 /CON
TRANSPORT
3F CULVERT (M)',T74,'SOURCE COST
EQUIPMENT ($)'/' OTHER COMPONENTS',2CON
1
1H0,T26,'LABOR ($)
1F14.0/ ' OVERHEAD,SUPERVISICN',FI4.0,F14.0 , T50,t'TOTAL CONSTRUCTICON
CON
20N COST FOR THIS PROJECT IS $ ',F12.0)
CON
CON
OUT(42)+
OUT(33)+
OUT(26)+
657
OUTPT(1)=OUT(3)+OUT(11)+CUT(19)+
CON
1 OUT(49)+ OUT(56)+ OUT(68)+ OUT(70)
1110
1120
1130
1140
1150
1160
1170
1180
1190
1200
1210
1220
1230
1240
1250
1260
1270
1280
1290
1300
1310
1320
1330
1340
1350
1360
1370
1380
1390
.1400
1410
1420
1430
1440
1450
1460
OUTPT(2)= OUT(4)+ OUT(12)+ CUT(20)+ OUT(27)+ OUT(34)+ OUT(43)
+OUT(50)+ OUT(57)+ OUT(69)+ OUT(71)
OUTPT(3)= OUT(8)+ OUT(16)+ CUT(23)+ CUT(30)+ OUT(39)+OUT(46)
+OUT(53)+ OUT(65)
1
OUTPT(4)= OUT (9)+ OUT(17)+ OUT(24)+ OUT(31)+ OUT(40)+
1
OUT(47)+ OUT(54) + OUT(66)
CON
CON
CON
CON
CON
CON
CON
C
CON
498
DO 133 1=1,4
CON
IF ( IODVO.NE.0O) GO TO 134
CON
OUTPT(I )=OUTPT( I)/ALIGN( 1)
CON
134
OUTPD(I)= OIJTP T( I )*DISC
CON
SUiM( I )=SUM( I )+ OUTPT( I)
CON
SUMD(I)=SUMD(I) +OUtTPD( I)
133
CON
TOTAL (1)=0UT0T( 1)+OUTPT(2)+OUTPT(3)+ OUTPT(4)
TOTAL(2)= OUTPD (1)+ OUTPD(2)+ OUTPD(3)+OUTPD(4)
CON
CON
TOTAL(3)= SIUM(1 )+ SUM(2)+ SUM(3)+ SUM(4)
CON
TOTAL(4)= SUMD( 1)+ SUMD(2)+ SUMD(3)+ SUMD(4)
CON
IF(OTRACE,GT.2 ) GO TO 658
CON
SUMD I ), I=1,4),
WRITF( IPRNT,303 ) ( OUTPT(I), OUTPD(I),SUM(I),
CON
(TOTAL(I),I=1 ,4 )
1
(PER KILOMETER )'I/ T30, 'THISCON
FORMAT(IHO, T40 ,' CCNSTRUCTION COSTS
303
1 PEPIOD ',T65,' SUM TO DATE'/ T25,' ACTUAL
0 ISCOUNTED' ,T55CON
DISCOUNTED
'/'
LABOR',T20,2(2Fl5.0
,5X)/ ' EQUIPMCON
2, 'ACTUAL
' MATERIAL ' ,T20,2(2Fl5.0,5X )/ ' TRANSPORTCON
3ENT',T20, 2(2F15 .0,5X)/
T20,2(2FI 5.0,5X ) )
CON
',T20, 2(2F15.0,5X)/ ' TOTAL',
4ATION
CON
658
CONTINUE
CON
C
CON
CON
COMPUTE FOREIGN CAPITAL UTILIZED IN CONSTRUCTION
C
CON
CON
FOREIGN COSTS ARE BROKEN INTO LABOR, SOURCE AND EQUIPMENT
CON
COMPUTE ACTUAL COST FOR PERIOD
CON
0.) GO TO 331
IF ( ECCN (2) .GT.
CON
DO 311 I=1,3
CON
II =(I -1)X*4 + 1
CON
311 OUTFR(I I)=FOREX( I+3)*OUTPT(I)
1
1470
1480
1490
1500
1510
1520
1530
1540
1550
1560
1570
1580
1500
1600
1610
1620
1630
1640
1650
1660
1670
1680
1690
1700
1710
1720
1730
1740
1750
1760
1770
1780
1790
1800
1810
1820
COMPUTE DISCOUNTED COST FOR THIS PERIOD
00 315 I=1,3
II= (I- 1)*4 +2
315 OUTFR(I I) = FORFX(I+3)*OUTPD( I
C
ACCUMUL ATED COST TO DATE
00 320 1=1,3
ll=(I-1 )*4+3
320 OUTFR(I I) =FOREX(I+3)*SUM(I)
C
COMPUTF ACCUMULATED COSTS DISCOUNTED TO DATE
DO 325 I=1,3
II= 1*4
325 OUTFR(II)= FOREX(T+3)*SUM 0(I)
C
TOTAL FORPEIGN COSTS FOR CCNSTRUCT ION
OUTFR(13) =0.
OUTFR(14) =0.
OUTFR(15) =0.
OUTFR(16) =0.
J=U
DO 327 I=13,16
J=J+1
DO 327 JJ=J,12,4
327 OUTFR(1) =OUTFR(I) +OUTFR (J J)
C
COMPUTE
FOREIGN COSTS IN DCLLARS
DO 330 I=1,16
330
OUTFRS(I)= OUTFR(I)-XRATE
332
331
CON
CON
CON
4 CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
CON
1830
1840
1850
1860
1870
1980
1890
1900
1910
1920
1930
1940
1950
1960
1970
1980
CON 1900
CON
CON
CON
CON
2000
2010
2020
2030
CON 2040
CON
CON
CON
CON
IF ( OTRACE.GT.0) GO TO 331
CON
WRITE(OU,332)
CON
1 FMONY,
(CUTFR(),IOUTFR(I+1),CUTFR(I+2),OUTFR(I÷+3),O IUTFRS( I )CON
I ,OUTFRS(I+1),OUTFRS(I+2),OUTFRS(I+3),
CON
I=1,13,4 )
FORMAT(1H0,T50,'OFFSHORE COSTS FOR CONSTRUCTION'/ T30,'IN ',3A4,
CON
) /CON
2 T80,'IN DOLLARS'/ T14,2(7X,'THIS PERIOD',15X,'SUM TO DATE ',7X
CON
2 T14, 4( 6X,'ACTUAL
DISCOUNTED' ) /
2 ' LABOR',T13,8F13.0/' FQUJIPMENT',T13,8Fl3.0/
' MATERIAL' ,T13
9 CON
)
CON
3 8F13.0 /'TOTAL',T13,8F13.0
RETURN
CON
2050
2060
2070
2080
2090
2100
2110
2120
2130
2140
2150
2170
2180
2190
194