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Travel outcome and performance: The effect of uncertainty on accessibility

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  • Hall, Randolph W.
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    Abstract

    An accessibility model is a conceptual tool which explains the interdependencies between the transportation infrastructure and human activities. Traditionally, theorists have based their accessibility models upon deterministic approximations. However, uncertainty in itself can affect whether an activity is accessible, and affect how one measures accessibility. In the first section of this paper, it is shown that travel time randomness interacts with the scheduling of human activities to define the region which is accessible to a traveler. In the second section, a problem is considered where a traveler must search among opportunities to locate a certain activity he desires. It is found that there exists an optimal cluster size which minimizes travel cost, the size being a decreasing function of the probability of locating the activity at any single opportunity.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 17 (1983)
    Issue (Month): 4 (August)
    Pages: 275-290

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    Handle: RePEc:eee:transb:v:17:y:1983:i:4:p:275-290

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    Cited by:
    1. Wu, Xing & (Marco) Nie, Yu, 2011. "Modeling heterogeneous risk-taking behavior in route choice: A stochastic dominance approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 896-915, November.
    2. Arnott, Richard & de Palma, Andre & Lindsey, Robin, 1999. "Information and time-of-usage decisions in the bottleneck model with stochastic capacity and demand," European Economic Review, Elsevier, vol. 43(3), pages 525-548, March.
    3. Bell, Michael G. H. & Cassir, Chris, 2002. "Risk-averse user equilibrium traffic assignment: an application of game theory," Transportation Research Part B: Methodological, Elsevier, vol. 36(8), pages 671-681, September.
    4. Lam, William H.K. & Shao, Hu & Sumalee, Agachai, 2008. "Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply," Transportation Research Part B: Methodological, Elsevier, vol. 42(10), pages 890-910, December.
    5. Nie, Yu (Marco), 2011. "Multi-class percentile user equilibrium with flow-dependent stochasticity," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1641-1659.
    6. Fosgerau, Mogens & Lindsey, Robin, 2013. "Trip-timing decisions with traffic incidents," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 764-782.
    7. Nie, Yu (Marco) & Wu, Xing & Dillenburg, John F. & Nelson, Peter C., 2012. "Reliable route guidance: A case study from Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 403-419.
    8. Hu Shao & William Lam & Mei Tam, 2006. "A Reliability-Based Stochastic Traffic Assignment Model for Network with Multiple User Classes under Uncertainty in Demand," Networks and Spatial Economics, Springer, vol. 6(3), pages 173-204, September.

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