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Incorporating land use in metropolitan transportation planning

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  • Waddell, Paul
  • Ulfarsson, Gudmundur F.
  • Franklin, Joel P.
  • Lobb, John
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    Abstract

    In current practice, very few Metropolitan Planning Agencies attempt to capture the effects of transportation system changes on land use, and the consequent feedback effects on transportation system performance, despite substantial evidence that these effects may be significant. In this paper, we present a case study on the application of UrbanSim, a detailed land use simulation model system, and its integration with a regional travel demand model in the Greater Wasatch Front area of Utah. Like several other metropolitan areas, this region has recently been confronted with legal challenges to proposed highway projects, drawing substantial scrutiny to the land use-transportation connection. We describe the UrbanSim model specification, results from model estimation, and sensitivity analyses conducted with the combined land use and travel model system. The results of the sensitivity analysis suggest that accounting for the land use effects of a regional transportation plan may produce significant shifts in key transportation evaluation measures such as vehicle miles traveled, vehicle hours traveled, and hours of congestion delay.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 41 (2007)
    Issue (Month): 5 (June)
    Pages: 382-410

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    Handle: RePEc:eee:transa:v:41:y:2007:i:5:p:382-410

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    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, Spring.
    2. Timothy J. Bartik, 1991. "Who Benefits from State and Local Economic Development Policies?," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wbsle, December.
    3. Paul Waddell, 2000. "A behavioral simulation model for metropolitan policy analysis and planning: residential location and housing market components of UrbanSim," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 27(2), pages 247-263, March.
    4. Wheaton, William C., 1977. "A bid rent approach to housing demand," Journal of Urban Economics, Elsevier, vol. 4(2), pages 200-217, April.
    5. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-99, June.
    6. Beckman, Richard J. & Baggerly, Keith A. & McKay, Michael D., 1996. "Creating synthetic baseline populations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(6), pages 415-429, November.
    7. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    8. J Landis & M Zhang, 1998. "The second generation of the California urban futures model. Part 1: Model logic and theory," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 25(5), pages 657-666, September.
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    Cited by:
    1. Efthymiou, D. & Antoniou, C., 2013. "How do transport infrastructure and policies affect house prices and rents? Evidence from Athens, Greece," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 1-22.
    2. Brian Lee & Paul Waddell, 2010. "Residential mobility and location choice: a nested logit model with sampling of alternatives," Transportation, Springer, vol. 37(4), pages 587-601, July.
    3. Marko Kryvobokov & Aurélie Mercier & Alain Bonnafous & Dominique Bouf, 2013. "Simulating housing prices with UrbanSim: predictive capacity and sensitivity analysis," Letters in Spatial and Resource Sciences, Springer, vol. 6(1), pages 31-44, March.
    4. Poulicos Prastacos & Nektarios Chrysoulakis, 2011. "Urban Atlas, land use modelling and spatial metric techniques," ERSA conference papers ersa11p1406, European Regional Science Association.
    5. Sevcíková, Hana & Raftery, Adrian E. & Waddell, Paul A., 2011. "Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 540-553, July.
    6. Canca, David & Zarzo, Alejandro & Algaba, Encarnación & Barrena, Eva, 2013. "Macroscopic attraction-based simulation of pedestrian mobility: A dynamic individual route-choice approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 428-442.
    7. Chorus, Caspar G. & Timmermans, Harry J.P., 2009. "Measuring user benefits of changes in the transport system when traveler awareness is limited," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 536-547, June.

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