An action recommendation system uses reinforcement learning that provides a next action recommendation to a traffic controller to give to a vehicle pilot such as an aircraft pilot. The action recommendation system uses data of past human actions to create a reinforcement learning model and then uses the reinforcement learning model with current ABS-B data to provide the next action recommendation to the traffic controller. The action recommendation system may use an anisotropic reward function and may also include an expanding state space module that uses a non-uniform granularity of the state space.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Traffic control with reinforcement learning


    Beteiligte:

    Erscheinungsdatum :

    2022-08-09


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



    TRAFFIC CONTROL WITH REINFORCEMENT LEARNING

    GANTI RAGHU KIRAN / SRIVASTA MUDHAKAR / RAO VENKATESH ASHOK RAO et al. | Europäisches Patentamt | 2020

    Freier Zugriff

    Reinforcement Learning with Explainability for Traffic Signal Control

    Rizzo, Stefano Giovanni / Vantini, Giovanna / Chawla, Sanjay | IEEE | 2019


    Deep reinforcement learning traffic light control method

    KONG YAN / LI YING / CHIH-CHAO YANG | Europäisches Patentamt | 2024

    Freier Zugriff

    Deep Reinforcement Learning-based Traffic Signal Control

    Ruan, Junyun / Tang, Jinzhuo / Gao, Ge et al. | IEEE | 2023