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Non-expected Route Choice Model under Risk on Stochastic Traffic Networks

Author

Listed:
  • Xiangfeng Ji

    (Southeast University)

  • Xuegang (Jeff) Ban

    (University of Washington
    Shanghai Maritime University)

  • Mengtian Li

    (Southeast University)

  • Jian Zhang

    (Southeast University)

  • Bin Ran

    (Southeast University
    University of Wisconsin)

Abstract

In this paper, we propose a novel non-expected route travel time (NERTT) model, which belong to the rank-dependent expected utility model. The NERTT consists of two parts, which are the route travel time distribution and the distortion function. With the strictly increasing and strictly concave distortion function, we can prove that the route travel time in the proposed model is risk-averse, which is the main focus of this paper. We show two different reduction methods from the NERTT model to the travel time budget model and mean-excess travel time model. One method is based on the properly selected distortion functions and the other one is based on a general distortion function. Besides, the behavioral inconsistency of the expected utility model in the route choice can be overcome with the proposed model. The NERTT model can also be generalized to the non-expected disutility (NED) model, and some relationship between the NED model and the route choice model based on the cumulative prospect theory can be shown. This indicates that the proposed model has some generality. Finally, we develop a non-expected risk-averse user equilibrium model and formulate it as a variational inequality (VI) problem. A heuristic gradient projection algorithm with column generation is used to solve the VI. The proposed model and algorithm are tested on some hypothetical traffic networks and on some large-scale traffic networks.

Suggested Citation

  • Xiangfeng Ji & Xuegang (Jeff) Ban & Mengtian Li & Jian Zhang & Bin Ran, 2017. "Non-expected Route Choice Model under Risk on Stochastic Traffic Networks," Networks and Spatial Economics, Springer, vol. 17(3), pages 777-807, September.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:3:d:10.1007_s11067-017-9344-3
    DOI: 10.1007/s11067-017-9344-3
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    4. Xinming Zang & Zhenqi Guo & Jingai Ma & Yongguang Zhong & Xiangfeng Ji, 2021. "Target-Oriented User Equilibrium Considering Travel Time, Late Arrival Penalty, and Travel Cost on the Stochastic Tolled Traffic Network," Sustainability, MDPI, vol. 13(17), pages 1-22, September.
    5. Ma, Jie & Xu, Min & Meng, Qiang & Cheng, Lin, 2020. "Ridesharing user equilibrium problem under OD-based surge pricing strategy," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 1-24.
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    7. 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).
    8. Xiangfeng Ji & Xiaoyu Ao, 2021. "Travelers’ Bi-Attribute Decision Making on the Risky Mode Choice with Flow-Dependent Salience Theory," Sustainability, MDPI, vol. 13(7), pages 1-24, April.
    9. Qinghui Xu & Xiangfeng Ji, 2020. "User Equilibrium Analysis Considering Travelers’ Context-Dependent Route Choice Behavior on the Risky Traffic Network," Sustainability, MDPI, vol. 12(17), pages 1-25, August.

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