Discretionary lane change (DLC) is a basic but complex maneuver in driving, which aims at reaching a faster speed or better driving conditions, e.g., further line of sight or better ride quality. Although modeling DLC decision-making has been studied for years, the impact of human factors, which is crucial in accurately modelling human DLC decision-making strategies, is largely ignored in the existing literature. In this paper, we integrate the human factors that are represented by driving styles to design a new DLC decision-making model. Specifically, our proposed model takes not only the contextual traffic information but also the driving styles of surrounding vehicles into consideration and makes lane-change/keep decisions. Moreover, the model can imitate human drivers’ decision-making maneuvers by learning the driving style of the ego vehicle. Our evaluation results show that the proposed model captures the human decision-making strategies and imitates human drivers’ lane-change maneuvers, which can achieve 98.66% prediction accuracy. Moreover, we also analyze the lane-change impact of our model compared with human drivers in terms of improving the safety and speed of traffic.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Learning-Based Discretionary Lane-Change Decision-Making Model With Driving Style Awareness


    Beteiligte:
    Zhang, Yifan (Autor:in) / Xu, Qian (Autor:in) / Wang, Jianping (Autor:in) / Wu, Kui (Autor:in) / Zheng, Zuduo (Autor:in) / Lu, Kejie (Autor:in)


    Erscheinungsdatum :

    01.01.2023


    Format / Umfang :

    2091141 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    A Learning-based Discretionary Lane-Change Decision-Making Model with Driving Style Awareness

    Zhang, Yifan / Xu, Qian / Wang, Jianping et al. | ArXiv | 2020

    Freier Zugriff

    Safe Hybrid-Action Reinforcement Learning-Based Decision and Control for Discretionary Lane Change

    Xu, Ruichen / Liu, Xiao / Xu, Jinming et al. | ArXiv | 2024

    Freier Zugriff



    Modeling of decision-making behavior for discretionary lane-changing execution

    Jianqiang Nie / Jian Zhang / Wan, Xia et al. | IEEE | 2016