دانلود مقاله انگلیسی رایگان:رویکرد یادگیری تقویت چند هدفه برای بهبود ایمنی در تقاطع ها با کنترل سیگنال ترافیک تطبیقی - 2020
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  • Multi-Objective reinforcement learning approach for improving safety at intersections with adaptive traffic signal control Multi-Objective reinforcement learning approach for improving safety at intersections with adaptive traffic signal control
    Multi-Objective reinforcement learning approach for improving safety at intersections with adaptive traffic signal control

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Multi-Objective reinforcement learning approach for improving safety at intersections with adaptive traffic signal control


    ترجمه فارسی عنوان مقاله:

    رویکرد یادگیری تقویت چند هدفه برای بهبود ایمنی در تقاطع ها با کنترل سیگنال ترافیک تطبیقی


    منبع:

    Sciencedirect - Elsevier - Accident Analysis and Prevention, 144 (2020) 105655. doi:10.1016/j.aap.2020.105655


    نویسنده:

    Yaobang Gong*, Mohamed Abdel-Aty, Jinghui Yuan, Qing Cai


    چکیده انگلیسی:

    Adaptive traffic signal control (ATSC) systems improve traffic efficiency, but their impacts on traffic safety vary among different implementations. To improve the traffic safety pro-actively, this study proposes a safety-oriented ATSC algorithm to optimize traffic efficiency and safety simultaneously. A multi-objective deep reinforcement learning framework is utilized as the backend algorithm. The proposed algorithm was trained and evaluated on a simulated isolated intersection built based on real-world traffic data. A real-time crash prediction model was calibrated to provide the safety measure. The performance of the algorithm was evaluated by the realworld signal timing provided by the local jurisdiction. The results showed that the algorithm improves both traffic efficiency and safety compared with the benchmark. A control policy analysis of the proposed ATSC revealed that the abstracted control rules could help the traditional signal controllers to improve traffic safety, which might be beneficial if the infrastructure is not ready to adopt ATSCs. A hybrid controller is also proposed to provide further traffic safety improvement if necessary. To the best of the authors’ knowledge, the proposed algorithm is the first successful attempt in developing adaptive traffic signal system optimizing traffic safety.
    Keywords: Traffic safety | Adaptive Signal control | Multi-objective reinforcement learning | Deep learning


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 13
    حجم فایل: 2372 کیلوبایت

    قیمت: رایگان


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