Automated driving is one of the main trends in automotive field. However, existing algorithms for automated driving are mostly designed based on statistical rules without considering the onboard drivers' individual features, which may lead to human-vehicle inconsistency during driving. In order to meet the driving preferences of any individual driver rather than classify into several driving styles (e.g. aggressive, conservative, moderate), this paper proposes a policy-learning method based on generative adversarial imitation learning. Specifically, an imitation learning framework consisting of generators and discriminators is built to train a policy network. Then, expert models are established to acquire driving data based on characteristics of individual drivers. In addition, the feasibility of the method is verified under scenarios of car following and lane changing. Finally, the generalization ability of the method is verified compared to the behavioral cloning method. The results reveal that the proposed method is capable to mimic the personalized features of human drivers.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Personalized Decision-Making and Control for Automated Vehicles Based on Generative Adversarial Imitation Learning


    Beteiligte:
    Tang, Xinyue (Autor:in) / Yuan, Kang (Autor:in) / Li, Shangwen (Autor:in) / Yang, Shuo (Autor:in) / Zhou, Zewei (Autor:in) / Huang, Yanjun (Autor:in)


    Erscheinungsdatum :

    24.09.2023


    Format / Umfang :

    3204282 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Generative Adversarial Imitation Learning-Based Continuous Learning Computational Guidance

    Luo, Haowen / Lee, Chang-Hun / Li, Chaoyong et al. | IEEE | 2025


    Modeling Human Driving Behavior Through Generative Adversarial Imitation Learning

    Bhattacharyya, Raunak / Wulfe, Blake / Phillips, Derek J. et al. | IEEE | 2023


    Automatic parking method and system based on generative adversarial imitation learning

    ZHU JIACHENG / ZHANG ZONGCHANG | Europäisches Patentamt | 2020

    Freier Zugriff