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Reliable route guidance: A case study from Chicago

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  • Nie, Yu (Marco)
  • Wu, Xing
  • Dillenburg, John F.
  • Nelson, Peter C.

Abstract

Reliable route guidance can be obtained by solving the reliable a priori shortest path problem, which finds paths that maximize the probability of arriving on time. The goal of this paper is to demonstrate the benefits and applicability of such route guidance using a case study. An adaptive discretization scheme is first proposed to improve the efficiency in computing convolution, a time-consuming step used in the reliable routing algorithm to obtain path travel time distributions. Methods to construct link travel time distributions from real data in the case study are then discussed. Particularly, the travel time distributions on arterial streets are estimated from linear regression models calibrated from expressway data. Numerical experiments demonstrate that optimal paths are substantially affected by the reliability requirement in rush hours, and that reliable route guidance could generate up to 5–15% of travel time savings. The study also verifies that existing algorithms can solve large-scale problems within a reasonable amount of time.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:transa:v:46:y:2012:i:2:p:403-419
    DOI: 10.1016/j.tra.2011.10.008
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    Cited by:

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    2. Wu, Xing, 2015. "Study on mean-standard deviation shortest path problem in stochastic and time-dependent networks: A stochastic dominance based approach," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 275-290.
    3. Manseur, Farida & Farhi, Nadir & Nguyen Van Phu, Cyril & Haj-Salem, Habib & Lebacque, Jean-Patrick, 2020. "Robust routing, its price, and the tradeoff between routing robustness and travel time reliability in road networks," European Journal of Operational Research, Elsevier, vol. 285(1), pages 159-171.
    4. Zhao, Tingting & Nie, Yu (Marco) & Zhang, Yi, 2014. "Extended spectral envelope method for detecting and analyzing traffic oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 61(C), pages 1-16.

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