intro to travel demand

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

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: 

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: 

Overview “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”: 

“Demand” v. “Behavior” Demand Aggregate Forecast TRB: ADB40, Transportation Demand Forecasting Behavior Disaggregate Explain TRB: ADB10, Traveler Behavior and Values Both deal with people’s travel choices/patterns/trends

Why do People Travel?: 

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

Assumed Implications (1): 

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

Assumed Implications (2): 

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 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?: 

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

Why Would Travel be Intrinsically Desirable?: 

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

Assertion: 

Assertion Those characteristics apply not only to undirected (recreational) travel, but to directed travel as well varying by mode, purpose, individual, circumstance

Trends in Travel Demand: 

Trends in Travel Demand

Global Changes, 1960-1990: 

Global Changes, 1960-1990                                                                                                                                                                                                               Motorized mobility (pkm) per capita, 1960 and 1990. Source: Schafer, 1998 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

pkm by mode, 1970-2001 (EU-15): 

pkm by mode, 1970-2001 (EU-15) Source: European Commission, 2003

Ave. Annual Growth Rate of Cars and Their Use, 1970-90: 

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): 

Auto Travel, 1970-2001 (EU-15) Source: European Commission, 2003

Intra-European Airline Passenger-km, 1970-2001: 

Intra-European Airline Passenger-km, 1970-2001 Data source: Eurostat/DGTREN. Source of figure: CNT, 2004

International Airline Passengers, 1993-2001: 

International Airline Passengers, 1993-2001 Data source: Eurostat. Source of figure: CNT, 2004

Per Capita km, 2001: 

Per Capita km, 2001 Source: European Commission, 2003

Mobility as a Function of GDP: 

Mobility as a Function of GDP                                                                                                                                                                                                               Motorized mobility (car, bus, rail, and aircraft) per capita by world region vs GDP per capita, between 1960 and 1990. Source: Schafer, 1998 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

Car Ownership v. GDP: 

Car Ownership v. GDP                                                                                                                                                                                                               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 SAS: South Asia PAS: Other Pacific Asia CPA: Centrally Planned Asia and China

Projected Mobility, 2050: 

Projected Mobility, 2050                                                                                                                                                                                                               Historical and estimated future total global mobility by mode in 1960, 1990, 2020 and 2050. Source: Schafer and Victor, 2000

Projected Mobility, 2050: 

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

Modeling Travel Demand/Behavior: 

Modeling Travel Demand/Behavior

Regional Travel Demand Forecasting (RTDF) (1): 

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): 

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): 

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: 

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

Disaggregate Behavioral Models/Tools: 

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: 

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

Discrete Choices of Work/Commute Engagement/Location: 

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

Disaggregate Behavioral Models/Tools: 

Disaggregate Behavioral Models/Tools ANOVA, regression Discrete choice (resid. loc., auto own., # of trips, destination, mode, route, combinations) Hazard models (activity durations, 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: 

Structural Model of Mobility Preferences/Behavior

Structural Model of Telecom/ Travel Relationships: 

Endogenous Variable Category Travel Demand Exogenous Variable Category Telecommuni-cations Demand Transporta-tion System Infrastructure Telecommuni- cations System Infrastructure Travel Costs Telecommuni-cations Costs Economic Activity Structural Model of Telecom/ Travel Relationships Land Use

Policy Measures and Travel Behavior: 

Policy Measures and Travel Behavior

When you think about it, virtually ALL policies are intended to affect behavior, whether they are ...: 

When you think about it, virtually ALL policies are intended to affect behavior, whether they are ... … supply-oriented, or demand-oriented

Supply-oriented Policies: 

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: 

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: 

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: 

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?: 

Other Questions? plmokhtarian@ucdavis.edu www.its.ucdavis.edu/telecom/ Slide borrowed from David Ory

Selected References: 

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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