Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
ASSIGNMENT TECHNIQUES FOR NETWORKS WITH JUNCTION
MODELLING
ABSTRACT
The modelling of congested urban road networks has been the subject of ongoing
research around the world for some time. A variety of methods have been developed
with varying levels of success and accuracy. A fundamental issue has been the trade off
between obtaining results that can be interpreted for strategic planning purposes, and the
need to represent traffic operations accurately at a local level. Many cities require a
flexible modelling tool that is capable of assessing both.
Ove Arup & Partners have recently developed and validated an EMME/2 model to
assess transport projects for the Auckland City, New Zealand that incorporates detailed
representation of junction delay, which draws on previous work undertaken by RO
Hill(1). The research and development of the modelling tool highlighted many important
modelling issues.
This paper discusses the issues related to congested assignment model development and
describes an approach to achieve the objectives of city-wide models. Topics discussed
include:





assignment methods;
stability and convergence;
appropriate level of detail for citywide models;
link and turn penalty functions; and
delay functions at signalised junctions.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
ASSIGNMENT TECHNIQUES FOR NETWORKS WITH JUNCTION
MODELLING
AUTHORS
Peter Dunn, B.Eng (Civil), MIE Aust,
Ove Arup & Partners New Zealand, Manager Transportation Planning New Zealand
Bruce Johnson, B.Eng (Hons), M.Eng.Sc, MIE Aust
Ove Arup & Partners, Manager Transportation Planning South-East Australasia;
Contact Details
Ove Arup & Partners New Zealand Ltd
PO Box 2503
Auckland 1
New Zealand
Phone +64 9 309 4713
Fax +64 9 307 3917
Email: peter.dunn@arup.com
INTRODUCTION
The representation of congested road networks for the purposes of evaluating alternative
traffic scenarios has been a continuing area of transport modelling research for some
time. Increasing desire by traffic authorities to assess the network effects of localised
traffic projects at a strategic level has lead to more detailed and sophisticated
assessment tools being developed.
Assignment convergence is a critical issue to ensure that comparisons between
alternative scenarios represent real differences of network supply or travel demand and
not varying degrees of convergence that may lead to erroneous cost-benefit analysis.
Many different algorithms and assignment methodologies have been developed and
used. However for the purposes of this paper we have divided techniques into two broad
categories, where travel cost is expressed either as a function of:


link flows (Type1); or
link flows, and turning volumes or capacity at junctions (Type 2).
Traditionally Type 1 models have proven popular, as a unique assignment solution is
obtainable using equilibrium algorithms. However when applied to congested urban
networks the level of network detail is limited without junction delay being represented.
Type 2 models can provide a finer level of detail. However to reach a converged
equilibrium solution Type 2 models require turn delay functions that predominantly
relate to the assigned volume on that approach link only (Type 2a). Where the function
strongly relates to assigned volumes on competing links at a junction (Type 2b) there is
no known minimisation technique. Type 2a functions make the realistic representation
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
of turning movement delays difficult when the test scenario predicts significantly
changed flow patterns on competing links at a junction, whilst Type 2b functions can
result in convergence problems. The chosen methodology is very much dependant on
the objectives of the model.
There has been much work undertaken in Auckland, New Zealand relating to Type 2
models. Arup have recently validated an EMME/2 traffic model for Auckland City
Council that required a new procedure to be developed. This required research into
different techniques to represent delay at junctions. This paper discusses junctionmodelling issues and outlines a process using EMME/2 that achieves the objectives of a
sub-regional traffic model, using the Auckland model as an example.
BACKGROUND
Auckland Model Hierarchy
Auckland has a well-defined model hierarchy. At the highest level there is the Auckland
Regional Transport (ART) model, a 4-step EMME/2 model capable of assessing
transport strategies at a regional level. There are four city councils in the Auckland
region. Each has developed, or is in the process of developing, more detailed subregional traffic models capable of being used to assess the impact of individual projects
at a citywide level. Figure 1 illustrates the model hierarchy.
ART Model
Auckland Regional Council
Public Transport
Assessment Model
Subregional Traffic Models
Auckland City
(being developed)
Manukau City
Waitakerie City
North Shore City
Project Models
Specific Projects
Auckland Model Hierarchy
Figure 1
Whilst the ART model provided the basis for the development of a regional wide
strategy, the network and zoning detail was too coarse for the assessment of individual
schemes. The Auckland planning authorities saw the need to develop more detailed,
local road network assignment models based on the ART model to assess and evaluate
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
road and traffic management projects. These became known as sub-regional models.
The Auckland Regional Council (ARC) provides the cities with traversals of their
vehicle trip matrices from the ART model for use in the subregional models. The
subregional models are essentially assignment only models.
Sub-regional Traffic Model Development
Objectives
The objectives of the sub-regional models are to:






assess impacts of regional transport strategies on the road network, to a level where
appropriate mid-block lane requirements, junction control and signal timing
strategies can be identified;
estimate design traffic volumes for transport projects;
provide input to more detailed junction design programs such as SIDRA to assess
junction requirements;
define future traffic conditions in road corridors;
assess the effect of public transport measures on traffic flow; and
provide outputs for economic evaluation.
In particular, they aim to:



represent intersection delay for each movement;
include all roads with a significant through traffic function; and
apply a finer zone system to the vehicle trip matrices traversed (extracted) from the
ART model.
Initial Development
Initially a Type 2 model process named ASRTaM (Auckland Sub Regional Transport
Assessment Model) was developed within the EMME/2 framework by Waitakere City
Council. ASRTaM is a complex assignment process carried out in EMME/2, which
uses two Fortran programs (SIGMA and OPFLOW) to estimate optimum timings at
signals and opposing flows at priority junctions.
The ASRTaM process is documented in a previous paper by Hill
described below as it relates to the new process developed here:
(1)
and is briefly

an initial set of junction parameters is calculated based on an assignment assuming
no junction delay;

ASRTaM then carries out a full equilibrium assignment and recalculates the
opposing flows at priority junctions, before re-assigning. This is undertaken for a
specified number of iterations and represents the inner loop of the process;

once the inner loop is completed, the signalised intersection parameters are recalculated and the next iteration begins. This is the outer loop; and
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Peter Dunn & Bruce Johnson

Assignment Techniques for Networks with Junction Modelling
this process is repeated until the green splits (outer loop) and opposed flows (inner
loop) do not change significantly between equilibrium assignments. This is the
criterion for convergence.
The model process was initially developed using the Waitakere sub-regional traffic
model as a test-bed. Waitakere is located to the west of Auckland City, with a mix of
urban and rural environment. The network includes 36 signalised and 193 priority
intersections. Six full outer iterations (green split calculations) were necessary to
achieve convergence of the base year model.
Meanwhile Auckland City Council undertook extensive work in 1996 and 1997 to
validate their sub-regional model (called the Isthmus model) using the ASRTaM
process. The Isthmus model consists of 366 zones while the road network is represented
in more detail than the ART model, particularly around the CBD and inner areas. A
total of 423 intersections are modelled, of which 195 are signalised. Traffic conditions
within Auckland City are significantly more congested than Waitakere.
Figure 2 shows the extent of Auckland City’s model area.
ART Model
Isthmus Model
Auckland City Model Area
Figure 2
A validation report was produced in March 1997, however the validation did not meet
the requirements of the Council. Arup were appointed in September 1998 to review and
validate the Auckland City model.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
ISTHMUS MODEL ISSUES
An initial review of the Isthmus model revealed problems which made use of the model
difficult and validation of the model impossible using the ASRTaM process. They are
summarised below:

in order to obtain an acceptable converged assignment 141 (65%) of the 195
signalised intersections required their parameters, such as green splits, saturation
flows and cycle time, to be estimated externally and provided as fixed inputs to the
process. There are two issues here, firstly it compromised the ASRTaM approach
which aims to optimise signal strategies during the assignment and secondly it
requires a very significant external analysis of individual junction operations.
Importantly this also implies externally estimating parameters for at least 141
junctions in future scenario tests;

the process required 25 iterations of the outer loop, and 4 iterations of the inner loop
to achieve acceptable stability, requiring a total of 100 equilibrium assignments;

due to the above total run times ranged from 10 hours on a Pentium 166MHz to 4.5
hours on a Pentium 266MHz, resulting in slow and costly turn over of tests;

no consistent method was documented of estimating basic saturation flows for those
junctions with fixed parameters. Errors were found in the estimation of the shared
lane effect as applied to those intersections with fixed parameters;

a common volume delay function was applied to all links with minimal capacity
restraint. Whilst this is often not critical in congested urban networks, the Isthmus
network includes several motorway and arterial road links where the link capacity
does constrain traffic flows and speed. Further, only roads with a significant
through traffic function are modelled, and therefore there is a need to distinguish
between roads with different access and activity characteristics;

the use of external Fortran programs to estimate signal timings and opposed flows
placed constraints on alterations to the model procedures and validation of the
algorithms employed;

the database entry facility was inflexible; and

comparison of future year scenario tests revealed inconsistent results after 25
iterations of the outer loop, particularly on parallel routes and there were large
differences between alternative equilibrium iterations. A review of previous
iterations indicated that the model was not converging to a unique solution.
It was clear that the ASRTaM process in its current form could not practically or
reliably be applied to the Isthmus Model, and therefore an alternative model process
was developed to meet the objectives of the model.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
MODEL DEVELOPMENT
Methodology
We conducted a literature review of a small number of papers and studies that drew on
Arup’s international experience to better understand the attributes of various model
approaches.
The issues we were particularly interested in were:



is this an appropriate use of EMME/2? If not what are the options?;
what assignment procedure should be used, and what options are available?; and
what level of precision is appropriate?
Type 1 models have employed delay functions that relate to characteristics of that link.
Some of the models incorporate link based functions that reflect to some degree
intersection approach capacity and delay characteristics. Type 1 models result in a
diagonalised function for which there are known mathematical minimalisation
algorithms. Many urban models have been satisfactorily calibrated using link-based
functions to estimate junction delays as well as link delay.
Type 2 models that have turn delay functions relating to characteristics of another link at
an intersection have a non-diagonal relationship. If this relationship is strong,
researchers have not been able to develop a mathematically proven minimisation
method. Researchers have therefore explored other ways of estimating delays at
junctions. For example SATURN runs through an assignment and junction simulation
loop. However it lessens the impact of the non-diagonal effect by employing a factor
that reduces flows though the junction above saturation. This has a flow on effect
through the network. Even so a stable solution is still difficult to achieve in congested
large citywide networks. TRIPS on the other hand allows alternative assignment
techniques, such as volume averaging, which smoothes the variations between
iterations. Again a converged solution can be difficult to obtain.
There have been several attempts to model junction delay in EMME/2. All attempts we
know of doing this other than by functions that relate strongly to the traffic flow along
the link have resulted in unstable results on congested networks. It is clear however that
the structured nature of EMME/2 the software provides capability to develop a process
at least to the level of say TRIPS.
The review revealed that there is no clear consensus on the junction modelling issue,
except that a wide variety of techniques are used worldwide, which result in continuing
research and debate. Relating this to the needs of the Isthmus model, it was concluded:

given the objectives of the model, it would be beneficial to model turn delays that
are estimated by a non-diagonal relationship. In such cases the uniqueness of the
process must be proven;
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling

it is possible to produce a model in EMME/2 that will have the same capability as
other strategic model packages with junction modelling capability, as say TRIPS;

assignment methods such as updating the intersection parameters after a smaller
number of equilibrium iterations and continuing the assignment, and damping
processes such as volume averaging should be explored to assist convergence; and

linkages between EMME/2 and SATURN have been tried (5), but to our knowledge
were found to be unsatisfactory, and were not explored further in this study.
Linkages between a strategic model and a detailed junction model such as SIDRA have
been mooted, but not tried. SIDRA outputs have been used as inputs to congested
assignment models, but this has been achieved by manual methods. There is some
suggestion that this could be explored further.
MODEL PROCEDURE
Based on the review a new model procedure was developed. The elements of the
process are described in this section and a flowchart illustrating the process is displayed
in Figure 3.
Assignment Process
Several alternatives were investigated. The adopted method involved carrying out one
full equilibrium assignment using both link and turn delay functions and then updating
the turn delay parameters during the assignment at specified intervals. An issue was at
what interval would the model produce a relatively stable result, to enable the final
portion of the equilibrium to be completed.
Previous experience suggested that turn delay parameter updates after a small number of
iterations were likely to produce better results. We tested several alternatives, and
concluded that optimal results for this model were obtained with junction parameters
updated every five equilibrium iterations until the 50th iteration, then concluding the
assignment without updates to meet the equilibrium stopping criteria. The process
allows the user flexibility to specify different update intervals and stopping criteria.
However it is important that the update intervals are consistent for alternative scenario
tests. Figure 4 shows the model convergence of a typical Isthmus model run.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
Model Process
Figure 3
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
R e la tiv e G a p
140
120
%
100
80
60
40
20
0
0
10
20
30
40
50
60
70
80
60
70
80
I te r a ti o n N u m b e r
N o rm a lis e d G a p
45
40
m in/trip
35
30
25
20
15
10
5
0
0
10
20
30
40
50
I te r a ti o n N u m b e r
Figure 4
The effect of the parameter updates can be seen in both graphs, noting that the relative
gap cannot be calculated in the first iteration after an update. A comparison of the
second iteration after each update generally shows a progressively decreasing relative
gap. The assignment takes 73 iterations to converge to a relative gap of 0.5% and a
normalised gap of 0.1 after the final junction parameter update.
Importantly tests conducted on the Isthmus network have shown that different starting
assumptions for assignments produce exactly the same assignment. While the
mathematical evidence does not guarantee uniqueness of solutions for Type 2 models,
the experience with application of this model shows that in practice a unique solution is
obtainable.
The adoption of this assignment procedure was a major factor in reducing run times
from 4.5 hours to 10 minutes.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
Turn Delay Functions
Several different turn delay functions were assessed. The ASRTaM process had used a
conic function that aggregated the various junction parameters into the standard conic
form. This was quite an involved procedure using module 2.41 to aggregate the
parameters into the three available user turn attributes, and resulted in 32 different turn
penalty functions.
The turn delay function applied to signalised junctions in the Isthmus model is based on
the SIDRA (2) delay functions. As the SIDRA functions use conditional statements
curve fitting was necessary to define a continuous function in a form that could be read
by EMME/2. The function is shown graphically in Figure 5 for three green splits.
Signal Delay Functions
Comparison for s=1800 vph, C=120 sec, T = 2h
2.00
Delay (min)
Model u=0.25
SIDRA u=0.25
Model u=0.50
SIDRA u=0.50
Model u=0.75
SIDRA u=0.75
1.00
0.00
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Degree of Saturation
Figure 5
The benefits of this approach are:



only one signal delay function is necessary for a given progression condition;
it is consistent with the methodology used to assess junction operations in
Australasia; and
the overflow component of the SIDRA delay function is already in a conic form,
which aids convergence.
Volume Delay Functions
The process uses the link component of the volume delay functions specified in the
Auckland Regional Transport model, which are based on recent surveys carried out in
New Zealand (8). A further two volume delay functions were defined to represent flow
conditions on roads performing a more local function. In all, 15 volume delay functions
were defined.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
Junction Parameter Input Process
The process requires junction parameters to be read into extra attributes using module
2.41. Table 1 indicates the turn parameters and format required. In addition to the turn
parameters there are several node parameters required including junction control type
and cycle time.
Table 1: Extra Turn Attributes
Extra Turn
Attribute
@tpf
Description
Column
Default
Code
Options
1 - 12
1 – 20
21 –32
defines turn at junction
4
0
@t
critical gap (sec)
5
4
@ml
@sat
@pha
number of lanes
saturation flow (vph)
Phase A
6
7
8
1
1850
0
0,1
@phb
Phase B
9
0
0,1
@phc
Phase C
10
0
0,1
@phd
Phase D
11
0
0,1
@phe
Phase E
12
0
0,1
@phf
Phase F
13
0
0,1
@phg
Phase G
14
0
0,1
@u
@gmin
green split
Minimum Green Time (sec)
16
17
0
6
0 –1
0 – 120
@pr
Progression Flag
18
1
1,2,3
@I
@l
@flt
Intergreen Time (sec)
Lost Time (sec)
Free Left Turn Flag
19
20
21
5
4
0
0 – 120
0 – 120
1
@opprt
Opposed Right Turn Flag
22
0
0-8
@short
@share
Short Lane Length (m)
Shared Lane Flag
23
24
0
0
0 – 200
1
@ped
Pedestrian Phase
25
0
2
@phi
Proportion of bunched traffic
for priority intersections
26
0
0.05 - 1
Comments
4 leg Priority/Roundabout
5 leg Priority
4 leg Signals
For priority and roundabouts
Turn Lanes (incl shared lanes)
User specified saturation flow
Flag 1 if movement is allowed in Phase
A, otherwise 0
Flag 1 if movement is allowed in Phase
B, otherwise 0
Flag 1 if movement is allowed in Phase
C, otherwise 0
Flag 1 if movement is allowed in Phase
D, otherwise 0
Flag 1 if movement is allowed in Phase
E, otherwise 0
Flag 1 if movement is allowed in Phase
F, otherwise 0
Flag 1 if movement is allowed in Phase
G, otherwise 0
User specified green split proportion
Minimum Green is 15 secs with
parallel ped phase
1 = Average Progression
2 = Good Progression
3 = Bad Progression
1 = Free Left Turn (All intersection
types)
0
= No Opposed Turn
1 - 7 = phase no (A - G)
8
= 2 opposed phases
0
= No short lane
0 = No Shared Lane
1 = Movement shares lane
0 = No Parallel Pedestrian Phase
1 = Parallel Pedestrian Phase
2 = All red pedestrian phase
As per ASRTaM manual
Data entry has been simplified by the development of an Excel spreadsheet to produce
the standard input files required by the process.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
Signalised Intersection Module
This comprises three components:



cycle time selection;
saturation flow estimation; and
green time estimation.
Full use of the capabilities of the network calculator module is made here, particularly
the hierarchical tree related to attributes in an expression evaluation.
Cycle time selection
The cycle time is input as a node attribute for each signalised intersection. The choice
of cycle times needs to be considered by the user as a strategic network management
issue and should reflect considerations such as practical cycle times for signal linking
and pedestrian requirements.
The process allows the user the option to specify a maximum cycle time, with the
program estimating the optimum cycle time.
Saturation Flow Estimation
This macro undertakes the following steps:

it assumes a user-specified base saturation flow for different speed environments as
follows:
Conditions
VDF Functions
Basic Saturation Flow (vph)
12 - 13
1750
Good
1-5
1850
Very Good
6-8
2000
Poor

for shared lanes, it apportions saturation flow on the basis of the current assignment
for the shared turns;

for movements where the right turn is opposed, a user-specified factor is applied to
the base saturation flow. ARR123 recommends this factor should be 1/3 for
approximate analysis. This method avoids the need to use opposed flow directly to
influence the capacity of the turn and so is desirable from the viewpoint of
assignment convergence. There is potential to include the more detailed and
technically correct method which relates to the green time allocation amongst other
parameters, but we believe the model's precision does not warrant this;
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling

where short lane effects occur a factor is applied to the base saturation flow. This
again is based on the ARR123 method. The queue length is estimated, and a factor
applied to the basic saturation flow if the queue exceeds the lane length; and

an option is available that allows the user to specify the saturation flow as input and
ignore the shared, opposed right turn and short lane effects. This would allow
specific input from SIDRA for complicated combinations of lane sharing, short
lanes or phase arrangements.
Green Split Estimation
This is a separate macro that follows as closely as practical the equal degrees of
saturation approach documented in ARR123 which is the theoretical basis of SIDRA
that has been accepted as a standard throughout most of Australasia.
In summary, features of the process are that:










it allows the user to specify the cycle time;
it estimates the required green time for each movement at a junction;
the user specifies the minimum green time allocated to each movement. This is an
important constraint and limits the range of resultant green splits, hence aiding
convergence;
the user specifies the practical degree of saturation;
it calculates the required cycle time by extracting the maximum green time
estimated for each phase and intergreen time. As this is carried out on a phase by
phase basis, movements that occur in more than one phase have their time
apportioned equally to each phase. Although this is a simplification, it is considered
an appropriate approximation for a network model;
it estimates new green splits based on the above, but checks that the sum of the
minimum phase times is not greater than the cycle time, in which case the new cycle
time is used;
free left turns are allocated 100% green split;
if the required cycle time is greater than the maximum cycle time then green splits
are reallocated considering the minimum green time requirements;
pedestrian phases are allowed for; and
the user can choose to specify a green split.
Priority Intersection Module
This is similar to the ASRTaM process, except that the opposed flows are calculated
within EMME/2 using module 2.41 and the registers. Generally the priority function
performed satisfactorily and wasn’t a critical element of the model. It is intended that
both the priority and roundabout function be reviewed for future model revisions.
Output and Results Module
This macro produces standard reports and plots of the results of the assignment to
enable the model results to be easily assessed.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
The following reports are produced in ASCII format:


aggregate measures of network performance and screenline comparisons; and
junction parameters where the maximum delay of any of the turns at a junction is
estimated to be greater than 2 minutes.
The following measures are calculated for viewing as plots in module 2.13:




maximum delay at a junction;
average delay at a junction;
degree of saturation at a junction; and
average delay on a junction approach.
VALIDATION
The model was shown to be well validated to 1991 measured travel times and traffic
flows. In summary:

assigned flows were within 10% of measured traffic volumes across all seven
screenlines.
Figure 6 shows a comparison of assigned flows against 270 measured flows within
the model area. The scattergram shows that a good correlation has been achieved
between assigned and measure link flows, resulting in an R2 value of 0.98, and a
standard deviation of 360 veh/2h.
Link Volume Scattergram
Validated 1991 Morning Peak
14000
12000
Assigned Flows (veh/2 hours)

10000
y = 0.9798x + 18.926
R2 = 0.9768
8000
6000
4000
2000
0
0
2000
4000
6000
8000
10000
12000
14000
Measured Flow s (veh/2 hours)
Figure 6
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Peter Dunn & Bruce Johnson



Assignment Techniques for Networks with Junction Modelling
92% of links had a GEH of less than 12% (GEH is a form of the chi-square statistic
which is designed to be tolerant of large errors in low flows);
significant outliers were identified for further investigation; and
model estimated travel times along 18 corridors are within 2% of measured times.
In addition the model's response to increased demand and network changes is logical
and justifiable. Figure 7 demonstrates such an example for the 1996 demand case with
the addition of a recently constructed arterial road. The assigned flows were checked
against counts undertaken within the area of the scheme and were found to closely
match measured flows with only two of the 25 locations having a GEH greater than 10.
Example of Model Response
Figure 7
CONCLUSIONS
The project has demonstrated the practicality of applying a Type 2 model using
EMME/2. The model process was shown to meet the requirements of Auckland City
and there is potential to apply this process to other sub-regional models. We have
endeavoured to make the model as flexible as possible by allowing the user to specify
inputs at a basic or detailed level.
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
In conclusion:

the detailed nature of the ASRTaM methodology provided a basis for the
development of this process. However in its current form it could not be practically
or reliably applied to a congested network scenario;







we have improved on this process by:
incorporating all modules within EMME/2;
improving run times from 4.5 hours to 10 minutes;
producing a stable and converged assignment;
incorporating flexible input procedures;
providing for more detailed junction input if required, consistent with ARR123; and
providing standard outputs to make the results easily accessible;





further improvements we would like to make to the current process include:
simplification of short lane effect methodology;
revision of priority and roundabout junctions;
application of a priority function for left turn slip lanes; and
allowance for data entry using a GIS.




the limitations of the method are:
there is no allowance for queuing back effects from downstream junctions;
the same update intervals should be used when testing alternative scenarios; and
there is no allowance for spreading demand to other time periods when high delays
are predicted.
Overall Arup would appreciate feedback from others who have tried similar approaches
and would welcome opportunities to apply this technique elsewhere.
REFERENCES
1. RO Hill (1998) An Application of EMME/2 Auto Assignment with Detailed
Junction Modelling of Activity at Nodes
2. SIDRA 5 User Guide ARRB Transport Research, January 1998
3. Traffic Signals – Capacity and Timing Analysis, ARR123, 5th reprint 1993
4. Transfund New Zealand Limited, 1998, Project Evaluation Manual
5. Junction Modelling within EMME/2: Ian Taylor and Peter Willoughby, 1998
European EMME2 Users Conference
6. Review of Models Combining Traffic Assignment and Signal Control: Claudio
Meneguzzer, Journal of Transportation Engineering – March/April 1997
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Peter Dunn & Bruce Johnson
Assignment Techniques for Networks with Junction Modelling
7. Effect of Intersection Delay Modelling on the Performance of Traffic Equilibrium
Models: Koutsopoulos and Habbal 1993
8. ART Model: Road Speed Flow Relationships Working Paper 3, 1994, Auckland
Regional Council
ACKNOWLEDGMENTS
The authors acknowledge Auckland City Transport Planning for whom the project was
undertaken, and Dave Thompson and Simon Camm (Ove Arup & Partners London) for
their advice and review of the paper.
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