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A Review of Game Theory Models of Lane Changing

Author

Listed:
  • Ji Ang
  • David Levinson

    (TransportLab, School of Civil Engineering, University of Sydney)

Abstract

Driver lane-changing behaviours have a significant impact on the safety and the capacity of the vehicle-based traffic system. Therefore, modeling lane-changing maneuvers has become an essential component of driving behaviour analysis. Among microscopic LC models, game theory-based lane-changing models highlight the interaction of drivers, which reveal a more realistic image of driving behaviours compared to other classic models. However, the potential of game theory to describe the human driver’s lane-changing strategies is currently under-estimated. This paper aims to review the recent development of game-theoretic models that are classified according to their different methodologies and features. They are designed for both human-driven and autonomous vehicles, and we hope they can find applications in future AV industries.

Suggested Citation

  • Ji Ang & David Levinson, 2020. "A Review of Game Theory Models of Lane Changing," Working Papers 2022-01, University of Minnesota: Nexus Research Group.
    • Handle: RePEc:nex:wpaper:gametheorylanechanginglitreview
    DOI: 10.1080/23249935.2020.1770368
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    File URL: https://hdl.handle.net/2123/21348
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Yakup Çelikbilek & Sarbast Moslem, 2023. "A grey multi criteria decision making application for analyzing the essential reasons of recurrent lane change," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 916-941, June.
    3. Cunningham, Naomi & Conner, David & Reynolds, Travis W., 2023. "Anchor Institutions and Food Resilience: A Multiple Streams Approach," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 14(02), June.
    4. Guo, Wenfeng & Song, Xiaolin & Cao, Haotian & Zhao, Song & Yi, Binlin & Wang, Jianqiang, 2023. "Human-centered driving authority allocation for driver-automation shared control: A two-layer game-theoretic approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    5. Masek, Frantisek & Zemlicka, Jan, 2024. "Average inflation targeting: how far to look into the past and the future?," Working Paper Series 2955, European Central Bank.
    6. Jiang, Yangsheng & Tan, Li & Xiao, Guosheng & Wu, Yunxia & Yao, Zhihong, 2024. "Platoon-aware cooperative lane-changing strategy for connected automated vehicles in mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).
    7. Tianpei Tang & Yuntao Guo & Guohui Zhang & Hua Wang & Quan Shi, 2020. "Understanding the Interaction between Cyclists’ Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis," IJERPH, MDPI, vol. 17(22), pages 1-29, November.
    8. Chen, Kehua & Zhu, Meixin & Sun, Lijun & Yang, Hai, 2024. "Combining time dependency and behavioral game: A Deep Markov Cognitive Hierarchy Model for human-like discretionary lane changing modeling," Transportation Research Part B: Methodological, Elsevier, vol. 189(C).

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    More about this item

    Keywords

    lane-changing models; game theory; driver interaction; driver utility; autonomous vehicles;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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