human choices relevant to

transportation – travel behavior

analysis and beyond

Cynthia Chen

Presentation made to Goodchild’s CEE500 Seminar Course, UW, Nov. 4, 2009

presentation outline• Presentation objectives• Why are we interested in human

choices in transportation?• Where have we come along?• Conclusions

objectives of the presentation

• To give an overview of travel behavior analysis and beyond

• To answer any related questions

why human choices are relevant in transportation? (1)

It is a prerequisite of urban transport planning and policy analysis to be able to predict how urban residents respond to transport policy measures, or any change in the general travel environment. Some examples: – how do they respond to a 10% increase in transit

fare? – How many auto commuters will change their

departure times in response to congestion pricing? – How many households will buy a low-emission

vehicle when a price discount is offered as a government incentive?

why human choices are relevant in transportation? (2)

Future transportation investments are made based on our predictions of how people travel in time and space in the future, given the general demographic and economic trends in the region.

It is the recognition that travel is derived demand that makes us look beyond trips and delve into the activities that drive the trips.

so, we started asking questions on the activities:

• These are the questions on what, where, when, with whom, how, and why?

• We later discovered that they seem to be all connected because of history dependence (past is a prologue to the present and future)

to summarize, we started with this list (activity-based analysis):

• Main items of interest for activities: activity type, duration, destination

• Main items of interest for trips: departure time, mode choice, route choice

• Main items of interest for activity and travel patterns: scheduling and rescheduling

References: Pas (1985), Kitamura (1988), Axhausen and Garling (1992)Kitamura and Fujii (1997), Bhat and Koppelman (2003)

the initial list has led to many methodological developments:• Activity type/mode/location choice –

discrete choice models • Activity duration/departure time –

survival models• Route choice – algorithms on path

generation• Activity scheduling/rescheduling –

sequential or simultaneous logit models or heuristic models

Ben-Akiva and Lerman (1985)

Newer references are not provided here, but if you want them, see me after class.

Hensher and Mannering (1994)

Kitamura et al. (1997)

but that is not enough, and things get more complicated (1):

• The space-time context: the concepts of prism and fixities – Home and job locations as important

anchor points in our space-time prism– Development of “pegs” related research– Moving trips to tours– Daily activity and travel patterns

developed based on the prism concepts

Hagerstrand (1970)

but that is not enough, and things get more complicated (2):

• The household notion challenging the unitary household assumption – household interaction appears in:– Household task assignment– Home and job location choices– Mode choices– Etc.

Timmermans and Zhang (2009)

but that is not enough, and things get more complicated (3):

• The social context that has led to research into:– Lifecycle– Lifestyle– Gender-based behavior analysis– Ethnicity and immigrants– Age, cohorts and period effects– Etc.

England (1993); McLafferty and Preston (1996)

but that is not enough, and things get more complicated (4):

• The neighborhood effect hypothesis:– The built environment (density,

diversity, design, and accessibility)– The connection between physically

active travel modes and health– The relation to urban growth or

suburban sprawl– The use of land use to change behavior– Etc.

Ewing and Cervero (2001)

but that is not enough, and things get more complicated (5):

• Moving from households to social networks, we recognize the notion of peer influence, or the idea that we are part of a superorganism, a hivelike network that shapes our decisions

Carrasco and Miller (2006)

but that is not enough, and things get more complicated (6):

• Behavioral dynamics (behavioral changes over time):– Habitual behavior– Life course perspective– Response lags/leads– Behavioral unsymmetry– Etc.

Kitamura (1990)

but that is not enough, and things get more complicated (7):

• More detailed analyses more data hungry:– SP/SC designs– Use of GPS/GIS, cellphones, and web-

interface in surveys– Panel designs– Etc.

Hensher (1994); Bates (undated)

conclusionsthe field of travel behavior analysis

and beyond is really burgeoning!