Reinforcement learning approach to develop variable speed limit strategy using vehicle data and simulations

IF 2.8 3区工程技术 Q3 TRANSPORTATION

Journal of Intelligent Transportation Systems Pub Date : 2024-02-08 DOI:10.1080/15472450.2024.2312808

Yunjong Kim, Kawon Kang, Nuri Park, Juneyoung Park, Cheol Oh

引用次数: 0

Abstract

A variety of studies have been conducted to evaluate real-time crash risk using vehicle trajectory data and to establish active traffic safety management measures. Speed management is an effective ...

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利用车辆数据和模拟，采用强化学习方法制定变速限制策略

为了利用车辆轨迹数据评估实时碰撞风险并制定积极的交通安全管理措施，已经开展了多项研究。车速管理是一种有效的交通安全管理措施。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Intelligent Transportation Systems 工程技术-运输科技

CiteScore

8.80

自引率

19.40%

发文量

审稿时长

15 months

期刊介绍： The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new. The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption. The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.