Deep reinforcement learning has shown potential in autonomous driving decision-making. However, vehicle decision-making involves complex information, and limited state information often limits the ability of agents to make optimal decisions. We present a novel on-ramp decision-making method using the SAC (Soft Actor-Critic) algorithm, which integrates the driving intentions of surrounding vehicles. Our model captures the vehicle characteristics of the target lane and its adjacent lanes as the state space. Additionally, we develop a hybrid action space that combines discrete lateral actions with continuous longitudinal actions, enabling the agent to adapt more effectively to intricate driving scenarios. The efficacy of our approach is validated through simulations using SUMO (Simulation of Urban MObility) and real-world road datasets. Comparative analysis of experimental results illustrates that our model surpasses alternative approaches in terms of collision rate and success rate. Moreover, the model exhibits a stable success rate under various road traffic density conditions.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Deep Reinforcement Learning with Driving Intention for On-Ramp Decision-Making


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Lianqing (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Fu, Wenxing (Herausgeber:in) / Qu, Yi (Herausgeber:in) / Fang, Huazhen (Autor:in) / Liu, Li (Autor:in) / Gu, Qing (Autor:in) / Xiao, Xiaofeng (Autor:in) / Meng, Yu (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2024 ; Shenyang, China September 19, 2024 - September 21, 2024



    Erscheinungsdatum :

    12.04.2025


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Intelligent automobile decision-making method based on driving intention and deep reinforcement learning

    PEI XIAOFEI / LU SONGXIN / YANG BO | Europäisches Patentamt | 2024

    Freier Zugriff

    Deep reinforcement learning algorithm based ramp merging decision model

    Chen, Zeyu / Du, Yu / Jiang, Anni et al. | SAGE Publications | 2025



    Automatic driving decision-making method based on deep reinforcement learning

    LIU CHENGQI / LIU SHAOWEIHUA / ZHANG YUJIE et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    Automatic driving decision-making system based on deep reinforcement learning

    ZHENG XIAOYAO / YAO QINGHE / ZHANG JIANPENG et al. | Europäisches Patentamt | 2024

    Freier Zugriff