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A Second Order Stochastic Network Equilibrium Model, II: Solution Method and Numerical Experiments

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  • David Watling

    (Institute for Transport Studies, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, United Kingdom)

Abstract

Real traffic networks typically exhibit considerable day-to-day variations in traffic flows and travel times, yet these variations are commonly neglected in network performance models. Recently, two alternative theoretical approaches were proposed for incorporating stochastic flow variation in the equilibration of route choices: the stochastic process (SP) approach (Cantarella and Cascetta 1995) and the second order generalized stochastic user equilibrium (GSUE(2)) model (Watling 2002). The theoretical basis of the two approaches is contrasted, and the paper goes on to present a heuristic solution method for the GSUE(2) model, and two alternative simulation methods for the SP model, each applicable to the realistic case of probit-based choice probabilities. These solution methods are then applied to two realistic networks. Factors affecting convergence and reproducibility are first identified, followed by comparisons of the GSUE(2) and SP predictions. It is seen that a quasi-periodic behaviour commonly arises in the SP model, with the predictions radically different from the GSUE(2) model. However, by modifying the link performance functions in the overcapacity regime, the nature of the SP solution changes, and for a memory filter based on a large number of days' experience, its moments are seen to be approximated by those of the GSUE(2) model. Implications for the application of these models are discussed.

Suggested Citation

  • David Watling, 2002. "A Second Order Stochastic Network Equilibrium Model, II: Solution Method and Numerical Experiments," Transportation Science, INFORMS, vol. 36(2), pages 167-183, May.
  • Handle: RePEc:inm:ortrsc:v:36:y:2002:i:2:p:167-183
    DOI: 10.1287/trsc.36.2.167.564
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    References listed on IDEAS

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    Cited by:

    1. Martin L. Hazelton & David P. Watling, 2004. "Computation of Equilibrium Distributions of Markov Traffic-Assignment Models," Transportation Science, INFORMS, vol. 38(3), pages 331-342, August.
    2. Prakash, A. Arun & Seshadri, Ravi & Srinivasan, Karthik K., 2018. "A consistent reliability-based user-equilibrium problem with risk-averse users and endogenous travel time correlations: Formulation and solution algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 171-198.
    3. Hazelton, Martin L., 2022. "The emergence of stochastic user equilibria in day-to-day traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 102-112.
    4. Ma, Jie & Meng, Qiang & Cheng, Lin & Liu, Zhiyuan, 2022. "General stochastic ridesharing user equilibrium problem with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 162-194.
    5. Teppei Kato & Kenetsu Uchida & William H. K. Lam & Agachai Sumalee, 2021. "Estimation of the value of travel time and of travel time reliability for heterogeneous drivers in a road network," Transportation, Springer, vol. 48(4), pages 1639-1670, August.
    6. Crawford, F. & Watling, D.P. & Connors, R.D., 2017. "A statistical method for estimating predictable differences between daily traffic flow profiles," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 196-213.
    7. David Watling, 2002. "A Second Order Stochastic Network Equilibrium Model, I: Theoretical Foundation," Transportation Science, INFORMS, vol. 36(2), pages 149-166, May.

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