Reports from University of Central Florida Add New Data to Findings in Risk Management (Multi-objective Reinforcement Learning Approach for Improving Safety At Intersections With Adaptive Traffic Signal Control)

2020 SEP 28 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Data detailed on Risk Management have been presented. According to news originating from Orlando, Florida, by NewsRx correspondents, research stated, “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.”

Our news journalists obtained a quote from the research from the University of Central Florida, “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 real world 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.”

According to the news editors, the research concluded: “To the best of the authors’ knowledge, the proposed algorithm is the first successful attempt in developing adaptive traffic signal system optimizing traffic safety.”

For more information on this research see: Multi-objective Reinforcement Learning Approach for Improving Safety At Intersections With Adaptive Traffic Signal Control. Accident Analysis & Prevention, 2020;144():105655. Accident Analysis & Prevention can be contacted at: Pergamon-Elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Accident Analysis & Prevention - http://www.journals.elsevier.com/accident-analysis-and-prevention/)

The news correspondents report that additional information may be obtained from Yaobang Gong, University of Central Florida, Dept. of Civil Environmental & Construction Engineering, Orlando, FL 32816, United States. Additional authors for this research include Mohamed Abdel-Aty, Jinghui Yuan and Qing Cai.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2020.105655. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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