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Modeling the Commute Mode Share of Transit Using Continuous Accessibility to Jobs

Listed author(s):
  • Andrew Owen
  • David Levinson

    ()

    (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)

This paper presents the results of an accessibility-based model of aggregate commute mode share, focusing on the share of transit relative to auto. It demonstrates the use of continuous accessibility — calculated continuously in time, rather than at a single or a few departure times — for the evaluation of transit systems. These accessibility calculations are accomplished using only publicly-available data sources. A binomial logit model is estimated which predicts the likelihood that a commuter will choose transit rather than auto for a commute trip based on aggregate characteristics of the surrounding area. Variables in this model include demographic factors as well as detailed accessibility calculations for both transit and auto. The model achieves a rho^2 value of 0.597, and analysis of the results suggests that continuous accessibility of transit systems may be a valuable tool for use in modeling and forecasting.

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File URL: http://hdl.handle.net/11299/180066
File Function: Second version, 2015
Download Restriction: no

Paper provided by University of Minnesota: Nexus Research Group in its series Working Papers with number 000115.

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Date of creation: 2013
Publication status: Published in Transportation Research part A Volume 74, April 2015, Pages 110–122
Handle: RePEc:nex:wpaper:modelingcommutemodeshare
Contact details of provider: Postal:
Dept. of Civil Engineering, 500 Pillsbury Drive SE, Minneapolis, MN 55455

Phone: +01 (612) 625-6354
Fax: +01 (612) 626-7750
Web page: http://nexus.umn.edu

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References listed on IDEAS
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  1. Fan, Yingling & Guthrie, Andrew E & Levinson, David M, 2012. "Impact of light rail implementation on labor market accessibility: A transportation equity perspective," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(3), pages 28-39.
  2. Tilahun, Nebiyou & Levinson, David, 2011. "Work and home location: Possible role of social networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 323-331, May.
  3. Mizuki Kawabata, 2009. "Spatiotemporal dimensions of modal accessibility disparity in Boston and San Francisco," Environment and Planning A, Pion Ltd, London, vol. 41(1), pages 183-198, January.
  4. Matthew R. Graham & Mark J. Kutzbach & Brian McKenzie, 2014. "Design Comparison of LODES and ACS Commuting Data Products," Working Papers 14-38, Center for Economic Studies, U.S. Census Bureau.
  5. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
  6. Mizuki Kawabata, 2003. "Job access and employment among low-skilled autoless workers in US metropolitan areas," Environment and Planning A, Pion Ltd, London, vol. 35(9), pages 1651-1668, September.
  7. Mizuki Kawabata & Qing Shen, 2006. "Job accessibility as an indicator of auto-oriented urban structure: a comparison of Boston and Los Angeles with Tokyo," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 33(1), pages 115-130, January.
  8. Wu, Belinda M. & Hine, Julian P., 2003. "A PTAL approach to measuring changes in bus service accessibility," Transport Policy, Elsevier, vol. 10(4), pages 307-320, October.
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