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A Game-Theory-Based Approach to Modeling Lane-Changing Interactions on Highway On-Ramps: Considering the Bounded Rationality of Drivers

Author

Listed:
  • Weihan Chen

    (School of Transportation, Southeast University, Jiulonghu Campus, Nanjing 211100, China
    These authors contributed equally to this work.)

  • Gang Ren

    (School of Transportation, Southeast University, Jiulonghu Campus, Nanjing 211100, China)

  • Qi Cao

    (School of Transportation, Southeast University, Jiulonghu Campus, Nanjing 211100, China
    These authors contributed equally to this work.)

  • Jianhua Song

    (School of Transportation, Southeast University, Jiulonghu Campus, Nanjing 211100, China)

  • Yikun Liu

    (Faculty of Foreign Studies, Beijing Language and Culture University, Beijing 100083, China)

  • Changyin Dong

    (School of Transportation, Southeast University, Jiulonghu Campus, Nanjing 211100, China)

Abstract

In highway on-ramp sections, the conflictual interactions between a subject vehicle (merging vehicle) in the acceleration lane and a following vehicle (lagging vehicle) in the adjacent mainline can lead to traffic congestion, go–stop oscillations, and serious safety hazards. Human drivers combine their previous lane-changing experience and their perception of surrounding traffic conditions to decide whether to merge. However, the decisions that they make are not always optimal in specific traffic scenarios due to fuzzy perception and misjudgment. That is, they make lane-changing decisions in a bounded rational way. In this paper, a game-theory-based approach is used to model the interactive behavior of mandatory lane-changing in a highway on-ramp section. The model comprehensively considers vehicle interactions and the bounded rationality of drivers by modeling lane-changing behavior on on-ramps as a two-person non-zero-sum non-cooperative game with incomplete information. In addition, the Logit QRE is used to explain the bounded rationality of drivers. In order to estimate the parameters, a bi-level programming framework is built. Vehicle trajectory data from NGSIM and an unmanned aerial vehicle survey were used for model calibration and validation. The validation results were rigorously evaluated by using various performance indicators, such as the mean absolute error, root mean square error, detection rate, and false-alarm rate. It can be seen that the proposed game theory-based model was able to effectively predict merging and yielding interactions with a high degree of accuracy.

Suggested Citation

  • Weihan Chen & Gang Ren & Qi Cao & Jianhua Song & Yikun Liu & Changyin Dong, 2023. "A Game-Theory-Based Approach to Modeling Lane-Changing Interactions on Highway On-Ramps: Considering the Bounded Rationality of Drivers," Mathematics, MDPI, vol. 11(2), pages 1-16, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:2:p:402-:d:1033707
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    References listed on IDEAS

    as
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