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Stochastic user equilibrium with a bounded choice model

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  • Watling, David Paul
  • Rasmussen, Thomas Kjær
  • Prato, Carlo Giacomo
  • Nielsen, Otto Anker

Abstract

Stochastic User Equilibrium (SUE) models allow the representation of the perceptual and preferential differences that exist when drivers compare alternative routes through a transportation network. However, as an effect of the used choice models, conventional applications of SUE are based on the assumption that all available routes have a positive probability of being chosen, however unattractive. In this paper, a novel choice model, the Bounded Choice Model (BCM), is presented along with network conditions for a corresponding Bounded SUE. The model integrates an exogenously-defined bound on the random utility of the set of paths that are used at equilibrium, within a Random Utility Theory (RUT) framework. The model predicts which routes are used and unused (the choice sets are equilibrated), while still ensuring that the distribution of flows on used routes accords to a Discrete Choice Model. Importantly, conditions to guarantee existence and uniqueness of the Bounded SUE are shown. Also, a corresponding solution algorithm is proposed and numerical results are reported by applying this to the Sioux Falls network.

Suggested Citation

  • Watling, David Paul & Rasmussen, Thomas Kjær & Prato, Carlo Giacomo & Nielsen, Otto Anker, 2018. "Stochastic user equilibrium with a bounded choice model," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 254-280.
    • Handle: RePEc:eee:transb:v:114:y:2018:i:c:p:254-280
    DOI: 10.1016/j.trb.2018.05.004
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    Cited by:

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    2. Yuan, Quan & Ye, Yujian & Tang, Yi & Liu, Yuanchang & Strbac, Goran, 2022. "A novel deep-learning based surrogate modeling of stochastic electric vehicle traffic user equilibrium in low-carbon electricity–transportation nexus," Applied Energy, Elsevier, vol. 315(C).
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    4. Ji, Xiangfeng & Chu, Yanyu, 2020. "A target-oriented bi-attribute user equilibrium model with travelers’ perception errors on the tolled traffic network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    5. Li, Dawei & Feng, Siqi & Song, Yuchen & Lai, Xinjun & Bekhor, Shlomo, 2023. "Asymmetric closed-form route choice models: Formulations and comparative applications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 171(C).
    6. Mads Paulsen & Thomas Kjær Rasmussen & Otto Anker Nielsen, 2022. "Including Right-of-Way in a Joint Large-Scale Agent-Based Dynamic Traffic Assignment Model for Cars and Bicycles," Networks and Spatial Economics, Springer, vol. 22(4), pages 915-957, December.
    7. Ding, Hongxing & Yang, Hai & Xu, Hongli & Li, Ting, 2023. "Status quo-dependent user equilibrium model with adaptive value of time," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 77-90.
    8. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).

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