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Travel and Emissions Analysis of Sustainable Transportation Policies with Activity-Based Modeling
Although activity-based models (ABMs) are starting to be used for metropolitan area transportation planning and policy making, experience is lacking in the use of the wealth of information and measures that such models offer. This paper reports on the implementation of an advanced ABM developed for...
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Published in: | Transportation research record 2015-01, Vol.2531 (1), p.93-102 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Although activity-based models (ABMs) are starting to be used for metropolitan area transportation planning and policy making, experience is lacking in the use of the wealth of information and measures that such models offer. This paper reports on the implementation of an advanced ABM developed for the Tel Aviv, Israel, metropolitan area to analyze the various transport, activity, and emissions impacts of auto restraint, transit, and land use policies. The policy implications of various scenarios are presented. The results showed that a combination of aggressive pull-and-push measures to encourage more transit and less car use had only marginal impacts on total vehicle kilometers traveled, emissions, and greenhouse gas emissions. Other findings showed no synergic effects and suggested that some policies might have had unintended outcomes. All of the policies tested led to less congestion but increased accessibility at the same time; the increased accessibility attracted more trips to the city. Overall, this study showed that ABMs could provide important advantages in the analysis of various transport policies to improve sustainable transportation development and to enable detailed analyses of the synergic effects of various policies and their impact on many indicators. The paper advances the state of the practice of the use of ABMs for policy analysis, but much more experience and insight are needed on the best way to use the rich information and abundant measures obtained from such models. |
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ISSN: | 0361-1981 2169-4052 |
DOI: | 10.3141/2531-11 |