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Lane-changing model with dynamic consideration of driver's propensity

Author

Listed:
  • Xiaoyuan Wang

    (Institute of Intelligent Transportation, School of Transportation and Vehicle Engineering, Shandong University of Technology, Zib 255091, P. R. China)

  • Jianqiang Wang

    (State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, P. R. China)

  • Jinglei Zhang

    (Institute of Intelligent Transportation, School of Transportation and Vehicle Engineering, Shandong University of Technology, Zib 255091, P. R. China)

  • Xuegang Jeff Ban

    (Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute (RPI), 110 Eighth Street, Room JEC 4034, Troy, NY 12180-3590, USA)

Abstract

Lane-changing is the driver's selection result of the satisfaction degree in different lane driving conditions. There are many different factors influencing lane-changing behavior, such as diversity, randomicity and difficulty of measurement. So it is hard to accurately reflect the uncertainty of drivers' lane-changing behavior. As a result, the research of lane-changing models is behind that of car-following models. Driver's propensity is her/his emotion state or the corresponding preference of a decision or action toward the real objective traffic situations under the influence of various dynamic factors. It represents the psychological characteristics of the driver in the process of vehicle operation and movement. It is an important factor to influence lane-changing. In this paper, dynamic recognition of driver's propensity is considered during simulation based on its time-varying discipline and the analysis of the driver's psycho-physic characteristics. The Analytic Hierarchy Process (AHP) method is used to quantify the hierarchy of driver's dynamic lane-changing decision-making process, especially the influence of the propensity. The model is validated using real data. Test results show that the developed lane-changing model with the dynamic consideration of a driver's time-varying propensity and the AHP method are feasible and with improved accuracy.

Suggested Citation

  • Xiaoyuan Wang & Jianqiang Wang & Jinglei Zhang & Xuegang Jeff Ban, 2015. "Lane-changing model with dynamic consideration of driver's propensity," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(02), pages 1-19.
    • Handle: RePEc:wsi:ijmpcx:v:26:y:2015:i:02:n:s0129183115500151
    DOI: 10.1142/S0129183115500151
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    Cited by:

    1. Zhufei Huang & Zihan Zhang & Haijian Li & Lingqiao Qin & Jian Rong, 2019. "Determining Appropriate Lane-Changing Spacing for Off-Ramp Areas of Urban Expressways," Sustainability, MDPI, vol. 11(7), pages 1-15, April.

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