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1.
A longstanding question within the field of transportation demand management is the strength of the relationship between urban form and mobility behavior. Although several studies have identified a strong correlation between these variables, there is as yet scant evidence to support policy interventions that target land use as a means of influencing travel. To the contrary, some of the more recent research has cast skepticism on the proposition that the relationship is causative, recognizing the possibility that households endogenously self-select themselves into communities that support their preferences for particular transportation modes. Focusing on individual automobile travel, the present study seeks to contribute to this line of inquiry by estimating econometric models on a panel of travel-diary data collected in Germany between 1996 and 2003. Specifically, we employ the two-part model (2PM)—a procedure involving probit and OLS estimators—to assess the determinants of the discrete decision to use the car and the continuous decision of distance traveled. Beyond modeling variables that capture the urban form features that are commonly suggested to influence mobility behavior, including mixed use and public transit, this study employs instrumental variables to control for potential endogeneity emerging from the simultaneity of residential and mode choices. Unlike much of the work to date, our results suggest that urban form has a causative impact on car use, a finding that is robust to alternative econometric specifications.
Ralf HedelEmail:
  相似文献   

2.
The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.
T. Keith LawtonEmail:

Lawrence Frank   is an Associate Professor and Bombardier Chair in Sustainable Transportation at the University of British Columbia and a Senior Non-Resident Fellow of the Brookings Institution and Principal of Lawrence Frank and Company. He has a PhD in Urban Design and Planning from the University of Washington. Mark Bradley   is Principal, Mark Bradley Research & Consulting, Santa Barbara California. He has a Master of Science in Systems Simulation and Policy Design from the Dartmouth School of Engineering and designs forecasting and simulation models for assessment of market-based policies and strategies. Sarah Kavage   is a Senior Transportation Planner and Special Projects Manager at Lawrence Frank and Company. She has a Masters in Urban Design and Planning from the University of Washington and is a writer and an artist based in Seattle. James Chapman   is a Principal Transportation Planner and Analyst at Lawrence Frank and Company in Atlanta Georgia. He has a Masters in Engineering from the Georgia Institute of Technology. T. Keith Lawton   transport modeling consultant and past Director of Technical services, Metro Planning Department, Portland, OR, has been active in model development for over 40 years. He has a BSc. in Civil Engineering from the University of Natal (South Africa), and an M.S. in Civil and Environmental Engineering from Duke University. He is a member and past Chair of the TRB Committee on Passenger Travel Demand Forecasting.  相似文献   

3.
Los Angeles is well known around the world as an automobile-oriented low density community, yet recent transportation policies have emphasized greater capital investment in rail transportation than in highways, and recent policies have attempted to discourage automobile usage through transportation demand management. While these policies have accomplished small shifts toward public transport and somewhat lower dependence upon singly occupied automobilies for work commuting, the financial costs of these policy changes has been very large in relation to their benefits. Proper pricing of transportation alternatives, more creative use of new and emerging transportation technologies, and the provision of many more opportunities for simpler private sector transport services, would all appear to be more promising as cost-effective approaches to coping with congestion in Los Angeles than the current regional transportation policies.  相似文献   

4.
This paper discusses the need for a new approach to urban transportation modelling in recognition that at least in medium sized towns the choice of model is largely dominated by car availability.  相似文献   

5.
Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.  相似文献   

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