Introduction%20to%20Travel%20Demand/Behavior,%20or%20What%20about%20the%20People%20in%20Transportation? - PowerPoint PPT Presentation

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Introduction%20to%20Travel%20Demand/Behavior,%20or%20What%20about%20the%20People%20in%20Transportation?

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Introduction to Travel Demand/Behavior, or. What about the People ... Curiosity, variety-, adventure-seeking; conquest. Sensation of speed or even just movement ... – PowerPoint PPT presentation

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Title: Introduction%20to%20Travel%20Demand/Behavior,%20or%20What%20about%20the%20People%20in%20Transportation?


1
Introduction to Travel Demand/Behavior, orWhat
about the People in Transportation?
  • Prof. Patricia L. Mokhtarian,
  • Dept. of Civil Environmental Engineering
  • Institute of Transportation Studies
  • University of California, Davis
  • plmokhtarian_at_ucdavis.edu
  • www.its.ucdavis.edu/telecom/

2
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

3
Overview
  • Demand versus behavior
  • Why do people travel?
  • Trends in travel demand
  • Modeling travel demand/behavior
  • Policy measures and travel behavior
  • Summary and conclusions

4
Demand v. Behavior
Both deal with peoples travel choices/patterns/tr
ends
  • Demand
  • Aggregate
  • Forecast
  • TRB ADB40, Transportation Demand Forecasting
  • Behavior
  • Disaggregate
  • Explain
  • TRB ADB10, Traveler Behavior and Values

5
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 spatially-separated
    activities
  • Corollary Travel is a disutility, that people
    try to minimize

6
Assumed Implications (1)
  • Saved travel time is a benefit, hence a basis for
    valuing transportation improvements
  • THE largest benefit component in most
    cost-benefit analyses
  • We can reduce travel by
  • ... making it more expensive
  • congestion pricing, fuel taxes, parking pricing

7
Assumed Implications (2)
  • We can reduce travel by
  • bringing activities closer together
  • increasing density and mixture of land uses
  • using ICT to conduct the activity remotely
  • telecommuting, -conferencing, -shopping,
    -education, -medicine, -justice
  • We can better forecast travel by under-standing
    peoples activity engagement the so-called
    activity-based approach to modeling travel
    demand

8
But is that the only reason people travel -- to
get somewhere in particular?
9
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

10
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

11
Trends in Travel Demand
12
U.S. Trends, 1950-2006 (1950 100)
13
http//www.bts.gov/publications/bts_transportation
_trends_in_focus/2010_04_01/html/figure_03.html,
accessed 9/30/2011
14
http//www.bts.gov/publications/bts_transportation
_trends_in_focus/2010_04_01/html/figure_04.html,
accessed 9/30/2011
15
http//www.bts.gov/publications/special_reports_an
d_issue_briefs/special_report/2007_10_03/html/figu
re_01.html, accessed 9/30/2011
16
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
17
pkm by mode, 1970-2001 (EU-15)
Source European Commission, 2003
18
European Private Auto Passenger Travel, 1990-2008
19
European Rail Passenger Travel, 1990-2008
20
European Bus/Coach Passenger Travel, 1990-2008
21
Ave. Annual Growth Rate of Cars and Their Use,
1970-90
Source USDOT, 1997, Figure 10-2, p. 231
22
Auto Travel, 1970-2001 (EU-15)
Source European Commission, 2003
23
Intra-European Airline Passenger-km, 1970-2001
Data source Eurostat/DGTREN. Source of figure
CNT, 2004
24
International Airline Passengers, 1993-2001
Data source Eurostat. Source of figure CNT,
2004
25
Per Capita km, 2001
Source European Commission, 2003
26
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
27
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
28
Projected Mobility, 2050
                                                
                                                  
                                                  
                                                  
       
Historical and estimated future total global
mobility by mode in 1960, 1990, 2020 and
2050. Source Schafer and Victor, 2000
29
Projected Mobility, 2050
Per-capita and total mobility for 11 regions (and
share of global total) in 1960, 1990, 2020, and
2050 for the reference scenario. NAM N.
America AFR Sub-Saharan Africa LAM Latin
America CPA Centrally Planned Asia and
China WEU W. Europe SAS South Asia EEU E.
Europe PAS Other Pacific Asia FSU Former
Soviet Union PAO Other Pacific OECD MEA Middle
East and North Africa Source Schafer and
Victor, 2000
                                                  
                                          
30
Modeling Travel Demand/Behavior
31
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)

32
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)

33
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)

34
Other Aggregate Demand Models
  • 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

35
Disaggregate Behavioral Models/Tools
  • ANOVA, regression
  • Discrete choice (residential location, auto
    ownership, of trips, destination, mode, route,
    combinations)

36
Discrete Choices of Work/Commute
Engagement/Location
  • Work engagement work frequency commute
    frequency

37
Discrete Choices of Work/Commute
Engagement/Location
  • Work engagement commute engagement type of
    partial commute

38
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
    tele-commuting engagement)
  • Factor analysis TTP 200 (attitude/opinion
    measurement)
  • Structural equations modeling (relationships
    among attitudes, residential location, and travel
    behavior relationships between telecom and
    travel)

39
Structural Model of Mobility Preferences/Behavior
40
Structural Model of Telecom/ Travel Relationships
Socio-demographics
Economic Activity
Travel Demand
Telecommuni-cations Demand
Transporta-tion System Infrastructure
Telecommuni- cations System Infrastructure
Telecommuni-cations Costs
Travel Costs
Land Use
Endogenous Variable Category
Exogenous Variable Category
41
Relationships among Attitudes, Land Use, Travel
Behavior
42
Policy Measures and Travel Behavior
43
When you think about it, virtually ALL policies
are intended to affect behavior, whether they are
...
  • supply-oriented, or
  • demand-oriented

44
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

45
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

46
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

47
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?

48
Other Questions?
plmokhtarian_at_ucdavis.edu www.its.ucdavis.edu/telec
om/
Slide borrowed from David Ory
49
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.
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