The invention discloses a bottleneck area traffic flow optimization control method and system based on deep reinforcement learning, and the method achieves the collection of vehicle information on a road through the Internet of Vehicles, carries out the decision making through the deep reinforcement learning, finally obtains a variable speed limiting control strategy, and achieves the refined regional and lane-divided speed limiting control. The variable speed limit control mode is a universal method for solving the traffic bottleneck problem, the fixed bottleneck can be solved, the movable bottleneck can also be solved, and a comprehensive and effective solution is provided for traffic management.
本发明公开了基于深度强化学习的瓶颈区交通流优化控制方法及系统,通过车联网对道路上的车辆信息进行采集,利用深度强化学习进行决策,最终获得一个可变限速控制策略,实现了精细化的分区域和分车道限速控制。这种可变限速的控制方式是一种通用解决交通瓶颈问题的方法,既可以解决固定瓶颈,又可以解决移动瓶颈,为交通管理提供了全面而有效的解决方案。
Bottleneck area traffic flow optimization control method and system based on deep reinforcement learning
基于深度强化学习的瓶颈区交通流优化控制方法及系统
2024-11-22
Patent
Electronic Resource
Chinese
IPC: | G06Q Datenverarbeitungssysteme oder -verfahren, besonders angepasst an verwaltungstechnische, geschäftliche, finanzielle oder betriebswirtschaftliche Zwecke, sowie an geschäftsbezogene Überwachungs- oder Voraussagezwecke , DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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