Introduction to Travel
Demand/Behavior, or
What about the People in
Transportation?
Prof. Patricia L. Mokhtarian,
Dept. of Civil & Environmental Engineering
& Institute of Transportation Studies
University of California, Davis
plmokhtarian@ucdavis.edu
www.its.ucdavis.edu/telecom/
Premise
An understanding of individuals’ travel
behavior is important to:
 forecasting future travel demand
 evaluating the effectiveness of policies
 predicting the response to new technologies
or services
 anticipating possible unintended
consequences
Overview

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



“Demand” versus “behavior”
Why do people travel?
Trends in travel demand
Modeling travel demand/behavior
Policy measures and travel behavior
Summary and conclusions
“Demand” v. “Behavior”
Both deal with people’s travel choices/patterns/trends
 Demand
– Aggregate
– Forecast
– TRB: ADB40,
Transportation
Demand
Forecasting
 Behavior
– Disaggregate
– Explain
– TRB: ADB10,
Traveler
Behavior and
Values
Why do People Travel?
(Why did the chicken cross the road?)
 Duh – to get where they want to be???
 Hence, the truism that “Travel is a derived
demand” – i.e. the demand for travel is
derived from the demand for spatiallyseparated activities
 Corollary: Travel is a disutility, that people
try to minimize

Assumed Implications (1)

Saved travel time is a benefit, hence a basis
for valuing transportation improvements
– THE largest benefit component in most costbenefit analyses

We can reduce travel by…
– ... making it more expensive
»
congestion pricing, fuel taxes, parking pricing
Assumed Implications (2)

We can reduce travel by…
–
… bringing activities closer together
»
–
… using ICT to conduct the activity remotely
»

increasing density and mixture of land uses
telecommuting, -conferencing, -shopping,
-education, -medicine, -justice
We can better forecast travel by understanding people’s activity engagement – the
so-called “activity-based approach” to
modeling travel demand
But is that the only reason people
travel -- to get somewhere in
particular?
Why Would Travel be
Intrinsically Desirable?









Escape
Exercise, physical/mental therapy
Curiosity, variety-, adventure-seeking; conquest
Sensation of speed or even just movement
Exposure to the environment, information
Enjoyment of a route, not just a destination
Ability to control movement skillfully
Symbolic value (status, independence)
Buffer between activities, synergy with multiple
activities
Assertions

Those characteristics apply not only to
undirected (recreational) travel, but to
directed travel as well
– varying by mode, purpose, individual,
circumstance

Even if “derived”, travel can simultaneously
be intrinsically valued
– in which case, people will be less inclined to
reduce it than an evaluation of its “derived”
nature alone would suggest
Trends in Travel Demand
700
600
Y1
500
400
(1950 = 100)
VMT (cars+light trucks), Y1
12000
Transit passengers, Y1
10000
Airline domestic PMT, Y2
8000
Airline international PMT, Y2
6000
300
200
100
0
50 952 954 956 958 960 962 964 966 968 970 972 974 976 978 980 982 984 986 988 990 992 994 996 998 000 002 004 006
9
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2
4000
2000
0
Y2
U.S. Trends, 1950-2006
U.S. VMT 1990-2009
Vehicle Miles Traveled
Vehicle Miles Traveled - Seasonally Adjusted
300
250
billions
200
150
100
50
0
Oct-89
Jul-92
Apr-95
Jan-98
Oct-00
Jun-03
Mar-06
Dec-08
http://www.bts.gov/publications/bts_transportation_trends_in_focus/2010_04_01/html/figure_03.html, accessed 9/30/2011
U.S. VMT 2001-2009
Vehicle Miles Traveled
Vehicle Miles Traveled - Trend
300
250
billions
200
150
100
50
0
Oct-00
Feb-02
Jun-03
Nov-04
Mar-06
Aug-07
Dec-08
May-10
http://www.bts.gov/publications/bts_transportation_trends_in_focus/2010_04_01/html/figure_04.html, accessed 9/30/2011
U.S. VMT -- Percent Change Since 1970
Population
Real Personal Income
Passenger VMT
200%
180%
160%
140%
120%
100%
80%
60%
40%
20%
0%
1970
1975
1980
1985
1990
1995
2000
http://www.bts.gov/publications/special_reports_and_issue_briefs/special_report/2007_10_03/html/figure_01.html, accessed 9/30/2011
2005
Global Changes, 1960-1990
NAM: N. America
LAM: Latin America
WEU: W. Europe
EEU: E. Europe
FSU: Former Soviet
Union
MEA: Middle East and
North Africa
AFR: Sub-Saharan
Africa
CPA: Centrally Planned
Asia and China
SAS: South Asia
PAS: Other Pacific Asia
PAO: Other Pacific
OECD
Motorized mobility (pkm) per capita, 1960 and 1990.
Source: Schafer, 1998
pkm by mode, 1970-2001 (EU-15)
6000
Passenger Cars
Buses & Coaches
5000
Tram + Metro
Railway
Air
1000 mio pkm
4000
Total
3000
2000
1000
0
1970
1975
Source: European Commission, 2003
1980
1985
1990
1995
2000
European Private Auto
Passenger Travel, 1990-2008
Ave. Annual Growth Rate of
Cars and Their Use, 1970-90
Source: USDOT, 1997, Figure 10-2, p. 231
Auto Travel, 1970-2001 (EU-15)
800
B
DK
700
D
EL
E
1000 mio pkm
600
500
F
IRL
400
I
L
300
NL
A
P
200
FIN
S
100
0
1970
UK
1975
Source: European Commission, 2003
1980
1985
1990
1995
2000
Intra-European Airline
Passenger-km, 1970-2001
Data source: Eurostat/DGTREN. Source of figure: CNT, 2004
International Airline Passengers,
1993-2001
Data source: Eurostat. Source of figure: CNT, 2004
Mobility as a Function of GDP
NAM: N. America
LAM: Latin America
WEU: W. Europe
EEU: E. Europe
FSU: Former Soviet
Union
MEA: Middle East and
North Africa
AFR: Sub-Saharan
Africa
CPA: Centrally Planned
Asia and China
SAS: South Asia
PAS: Other Pacific Asia
PAO: Other Pacific
OECD
Motorized mobility (car, bus, rail, and aircraft) per capita by world region
vs GDP per capita, between 1960 and 1990. Source: Schafer, 1998
Car Ownership v. GDP
SAS: South
Asia
PAS: Other
Pacific Asia
CPA: Centrally
Planned Asia
and China
Estimated motorization rates for CPA, PAS and SAS, compared with the observed rise in motorization
in several countries. Source of historical data: United Nations, 1960; United Nations, 1993a and IRF, various years.
Source for figure: Schafer and Victor, 2000
Projected Mobility, 2050
Historical and estimated future total global mobility by mode in 1960, 1990, 2020 and 2050.
Source: Schafer and Victor, 2000
Modeling Travel
Demand/Behavior
Regional Travel Demand
Forecasting (RTDF) (1)
Or, the Urban Transportation Planning
System (UTPS)
 The workhorse of metropolitan area
planners (ECI 251)

– forecast demand
– evaluate alternatives

Calibrated with data from a large-scale
travel/activity diary survey (TTP 200)
Regional Travel Demand
Forecasting (RTDF) (2)

The model contains 4 stages or submodels,
corresponding to a set of choices that
individuals are assumed to make:
–
–
–
–
whether to travel (trip generation)
where to travel (trip distribution)
by what means (mode) to travel (mode choice)
by what route (route assignment)
Regional Travel Demand
Forecasting (RTDF) (3)

Example analysis tools used:
– cross-classification, regression (trip generation)
– gravity model (trip distribution)
– probabilistic discrete choice – ECI 254 (mode
choice)
– network optimization – ECI 257 (route
assignment)
Other Aggregate Demand Models

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Auto ownership
Nationwide vehicle-miles traveled (VMT)
Travel time – is there a “travel time budget”?
Fuel consumption
Air travel demand
TOOLS:
– Regression
– Time series
– Structural equations modeling
Disaggregate Behavioral
Models/Tools


ANOVA, regression
Discrete choice (residential location, auto ownership, #
of trips, destination, mode, route, combinations)
Discrete Choices of Work/Commute
Engagement/Location

Work engagement – work frequency –
commute frequency
choice
Non-worker
work
Part-time
worker
full-time
Fullycommuting
worker
Home-based
worker
Telecommuter
Compressedschedule
worker
Discrete Choices of Work/Commute
Engagement/Location

Work engagement – commute engagement –
type of partial commute
choice
work
Non-worker
Fullycommuting
worker
partial
commuter
Home-based
worker
Part-time
worker
Telecommuter
Compressedschedule
worker
Disaggregate Behavioral
Models/Tools
 ANOVA,
regression
 Discrete choice (resid. loc., auto own., # of trips,
destination, mode, route, combinations)
 Hazard models (activity durations, how long a
vehicle is owned, time till accident, length of telecommuting engagement)
 Factor analysis – TTP 200 (attitude/opinion
measurement)
 Structural equations modeling (relationships
among attitudes, residential location, and travel
behavior; relationships between telecom and travel)
Structural Model of Mobility
Preferences/Behavior
Relative Desired
Mobility
Mobility
Constraints
Personality
& Lifestyle
General Travel
Attitudes
Travel
Liking
Demographics
Objective
Mobility
Subjective
Mobility
Structural Model of Telecom/
Travel Relationships
Transportation System
Infrastructure
Sociodemographics
Economic
Activity
Travel
Demand
Telecommunications
Demand
Travel Costs
Endogenous Variable Category
Land Use
Exogenous Variable Category
Telecommunications
System
Infrastructure
Telecommunications Costs
Relationships among
Attitudes, Land Use, &
Travel Behavior
Attitudes
c
d
b
Residential
Choice (BE)
Socioeconomic &
Demographic Traits
e
a
Travel
Behavior
Policy Measures and Travel
Behavior
When you think about it,
virtually ALL policies are
intended to affect behavior,
whether they are ...
… supply-oriented, or
 demand-oriented

Supply-oriented Policies

Expand physical infrastructure
– Does this in itself stimulate the realization of
latent demand?
More effectively manage existing supply
(Transportation Supply Management, TSM)
 Increase supply or reduce costs

– to underserved populations
– of using non-auto modes
Demand-oriented Policies

Generally intended to reduce demand, by
– changing the cost signals (internalizing
externalities, i.e. raising costs!)
– changing land use planning to bring activities
closer together
– promoting ICT substitution

Collectively referred to as Transportation
Demand Management (TDM) strategies
Summary
People travel for many reasons besides the
obvious one; it is a fundamental human need
 Worldwide trends are toward more travel, not
just due to population growth, but per capita
 It is a challenge to balance the human need for
mobility against the need for sustainability
 We need to better understand the need to
travel for its own sake, and reasons behind
various travel decisions

– Implications for modeling, evaluation, policy
Discussion Questions
DOES virtual mobility reduce the need for
real mobility?
 How can we balance the human need for
mobility against the need for sustainability?
 Should policymakers try harder to
discourage “unnecessary” travel? What are
the most effective ways of doing so?
 Can people express the extent to which they
travel “for its own sake”?

Other
Questions?
plmokhtarian@ucdavis.edu
www.its.ucdavis.edu/telecom/
Slide borrowed from David Ory
Selected References
CNT (Conseil National des Transports, Observatory on Transport Policies and Strategies in Europe)
(2004) Bulletin Transports/Europe No. 11. Available at www.cnt.fr.
European Commission (2003) European Union Energy & Transport in Figures. Directorate-General for
Energy and Transport.
Handy, Susan (2002) Accessibility- vs. mobility-enhancing strategies for addressing automobile
dependence in the US. Prepared for the European Council of Ministers of Transport Roundtable 124,
on Transport and Spatial Policies, November 7-8, Paris.
Houseman, Gerald (1979) The Right of Mobility. Port Washington, NY: Kennikat Press.
Mokhtarian, Patricia L. & Cynthia Chen (2004) TTB or not TTB, that is the question: A review and
analysis of the empirical literature on travel time (and money) budgets. Transportation Research A
38(9-10), 643-675.
Mokhtarian, Patricia L. & Ilan Salomon (2001) How derived is the demand for travel? Some conceptual
and measurement considerations. Transportation Research A 35, 695-719.
Schafer, Andreas (1998) The global demand for motorized mobility. Transportation Research A 32(6),
455-477.
Schafer, Andreas and David G. Victor (2000) The future mobility of the world population.
Transportation Research A 34(3), 171-205.
U. S. Department of Transportation (1997) Transportation Statistics Annual Report 1997: Mobility and
Access. Washington, DC: USDOT Bureau of Transportation Statistics. Available at
http://www.bts.gov/publications/transportation_statistics_annual_report/1997/pdf/report.pdf.