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Aspects of commuting behavior: Preferred arrival time, use of information and switching propensity

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  • Caplice, Chris
  • Mahmassani, Hani S.

Abstract

This paper analyzes the results of a commuter behavior survey conducted in Austin, TX. Commuters' preferred arrival times at the workplace, use of traffic information and switching propensity (for both route and departure time) are discussed. Mathematical models are developed for each of these aspects relating them to three types of factors: traffic system characteristics, workplace conditions and individual attributes. The preferred arrival time at the workplace is modeled as a Poisson regression model, use of information as a binary logit function and switching decision as multinomial logit choice models. Comparisons are drawn between this sample and similar studies conducted in Seattle, WA.

Suggested Citation

  • Caplice, Chris & Mahmassani, Hani S., 1992. "Aspects of commuting behavior: Preferred arrival time, use of information and switching propensity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 26(5), pages 409-418, September.
  • Handle: RePEc:eee:transa:v:26:y:1992:i:5:p:409-418
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    Citations

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    Cited by:

    1. Chen, Ting-Yu & Chang, Hsin-Li & Tzeng, Gwo-Hshiung, 2001. "Using a weight-assessing model to identify route choice criteria and information effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(3), pages 197-224, March.
    2. Golledge, Reginald G & Zhou, Jack, 1999. "A GPS-based Analysis of Household Travel Behavior," University of California Transportation Center, Working Papers qt3hg1f5nb, University of California Transportation Center.
    3. Zhou, Jack & Golledge, Reginald, 1999. "A GPS-based Analysis Household Travel Behavior," University of California Transportation Center, Working Papers qt3zf8h075, University of California Transportation Center.
    4. Emmerink, Richard H. M. & Nijkamp, Peter & Rietveld, Piet & Van Ommeren, Jos N., 1996. "Variable message signs and radio traffic information: An integrated empirical analysis of drivers' route choice behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(2), pages 135-153, March.
    5. He, Sylvia Y., 2013. "Does flexitime affect choice of departure time for morning home-based commuting trips? Evidence from two regions in California," Transport Policy, Elsevier, vol. 25(C), pages 210-221.
    6. Kumar, Amit & Peeta, Srinivas, 2015. "A day-to-day dynamical model for the evolution of path flows under disequilibrium of traffic networks with fixed demand," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 235-256.
    7. Golledge, Reginald G. & Zhou, Jianyu, 2001. "GPS-Based Tracking of Daily Activities," University of California Transportation Center, Working Papers qt9jb438r2, University of California Transportation Center.
    8. Timmermans, Harry & van der Waerden, Peter & Alves, Mario & Polak, John & Ellis, Scott & Harvey, Andrew S. & Kurose, Shigeyuki & Zandee, Rianne, 2002. "Time allocation in urban and transport settings: an international, inter-urban perspective," Transport Policy, Elsevier, vol. 9(2), pages 79-93, April.
    9. Khoo, Hooi Ling & Asitha, K.S., 2016. "An impact analysis of traffic image information system on driver travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 175-194.

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