Investigating the Disaggregate Travel Behavior Effects of the Built Environment
Increasingly, changes in neighborhood and commercial area design are being proposed and
implemented in urban areas as solutions to transportation and environmental problems. Travel
behavior varies depending on the design of the built environment at both ends of the trip. It is
likewise affected by the quality and availability of transportation facilities and services, which
connect trip ends. The extent to which proposed changes in land use mix, density, and improvements in connectivity between complementary uses (live, work, play) increase transit and nonmotorized travel, reduce auto dependence, improve air quality, reduce fuel consumption, and benefit public heath is clearly worthy of both further exploration and translation into better
planning and analysis tools.
Research on the effects of the built environment on travel choice has become more
sophisticated over the last decade and now includes many detailed forms of household-, person-and trip-level analysis. However, further work is needed to refine and fill gaps in these analyses to make existing models more responsive and to develop new tools that more accurately predict
travel and other effects of urban form. Improvements in our ability to assess land use and
transportation relationships can be achieved both through recent gains in the quality of land use, travel, and transportation service data and through integration of these types of data in ways that are more comprehensive and readily consistent with available and developmental travel demand
Advanced parcel-level data on the built environment need to be fully and jointly
incorporated with disaggregate trip-level transportation data into analyses that predict how land use affects travel choice. Enhanced information ranging from microscale aspects of the built environment, on the one hand, to transportation system performance for peak, off-peak, and weekend travel on the other, is critical in better explaining travel behavior. The development of new and improved methods to incorporate these data into the travel demand modeling process is crucial for the creation of land use and transportation policies that will provide multiple favorable outcomes, including both mobility and health improvements.
The proposed research would quantify the effects of urban form and site design on a full range of
travel behavior and related choices in context with fully described data on transportation service
and the local built environment. The research would address the differences in revealed travel
behavior related to the built environment at the locations where travel takes place.
Phase I: Data Collection
A review of research related to the built environment and transportation service variables should be conducted. Urban areas with up-to-date household-travel and employer-based surveys should be identified. It is anticipated that as many as three areas could be involved in the study to enable testing for transferability of results. Existing and further exploratory research on residential and commercial neighborhood morphology and its classifications would be undertaken to identify promising indicators for use in the analysis. A typology would then be developed to classify urban areas into neighborhood types. Travel survey and employer-based survey results would be gathered for the case study areas. Using the classification, the data would then be stratified by neighborhood type. It is desired that a statistically sound sample for the built environment types be obtained. It will most likely be necessary to conduct additional surveys to ensure adequate coverage of built environment types.
Phase II: Analysis
The analysis phase would advance the understanding and quantification of the effects that the built environment has on travel behavior. This analysis would be accomplished through the use of trip-level transportation service data in conjunction with disaggregate socio-economic data
and other trip-end variables. Trip-end variables including accessibility as well as built environment variables should be considered in regional travel demand modeling. The most desirable analysis would address all urban modes of travel and the purpose of that travel. Various data preparations would obviously be the first step, bringing together trip data, person data, full travel path transportation service data (distance, travel times broken down by component, user costs, trip quality measures, etc.), and the built environment indictors refined in Phase I. Exploratory steps would follow, applying an array of statistical analyses to better understanding interrelationships between the different indicators of the built environment and travel demand. For example, exploratory evaluation approaches could include an error analysis of application results for baseline travel demand models prepared without built environment factors, analyzing possible correlation of underestimating and overestimating the different steps of travel estimation to measures of individual aspects of the built environment. Aspects of travel demand to be examined should include auto ownership; trip generation; trip distribution; mode choice, including nonmotorized transport and auto occupancy; and possibly transit mode of access and other parameters.
With this background, further steps could move the research into specifying and testing demand model formulations actually containing a full array of built environment variables. Both richly specified models and models constrained to variables for forecast deserve exploration.
This phase of research should not only seek to ultimately select and calibrate robust built environment variables, obtaining their statistics and coefficients, but also to derive built ennvironment travel elasticity’s for the various modes and purposes.
Phase III: Travel Model Recommendations and Policy Implications Based on Phase I and II results, recommendations would be formulated for translating the research findings into transportation and land use survey technique enhancements and regional travel demand model improvements. These could range from new measures and predictors of the built environment (including a typology of urban forms for data collection) to methods to bring these and other land use measures into travel demand models, including current regional four-step models (trip generation, distribution, mode choice, and assignment), microscale models, and beta-testing of new activity-based travel models reflective of differentiation between first-order mobility choices and second-order travel choices, tour and trip structure, and other advancements.
Policy implications would be addressed based on the Phase I and II findings. Elasticitys for potential use in sketch planning applications could be extracted. It would be highly desirable
to include in the Phase III activity the re-application of Phases I and II. This would abbreviate the developmental steps to a second and possibly a third urban region to address transferability issues. A document detailing the potential transportation, public health, environmental, land use policy, and analysis methods implications would be created.
Duration: 3 years
|Sponsoring Committee:||AMS50, Economic Development and Land Use
|Source Info:||ENVIRONMENTAL RESEARCH NEEDS CONFERENCE 2002|
TRANSPORTATION ENVIRONMENTAL RESEARCH NEEDS STATEMENTS
|Index Terms:||Travel behavior, City planning, Urban areas, Urban transportation, Built environment, Mode choice, Travel demand, Travel demand management, |
Pedestrians and Bicyclists|
Planning and Forecasting