Study on dynamic assessment and early warning model of expressway traffic flow risk

Guoqiang Li

doi:10.1117/12.2683922

14 June 2023 Study on dynamic assessment and early warning model of expressway traffic flow risk

Guoqiang Li

Proceedings Volume 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）; 127082S (2023) https://doi.org/10.1117/12.2683922
Event: 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 2023, Chongqing, China

Abstract

This paper studies the risk assessment of traffic flow on major highways under high-speed driving conditions and the safety warning after traffic incidents. Firstly, by analyzing the operation characteristics of the main line traffic flow and the evolution characteristics of the upstream traffic flow after the event, a collaborative control strategy for the dynamic assessment and accurate early warning of the main line traffic flow is proposed. Secondly, based on the operating speed, traffic flow and head-time distance state parameters of the main traffic flow, the risk assessment model of the main traffic flow is established, which provides an algorithm basis for the safe operation status evaluation and active control of the main traffic flow. Third, based on the driver’s reaction process after the traffic incident and the evolution process of main traffic flow, a traffic incident safety warning distance function is proposed, which provides a quantitative function for the accurate early warning and prevention of traffic accidents in the upstream traffic flow after traffic incidents. Through the dynamic assessment and control of operation risks of expressway main line traffic flow, the accurate risk warning of expressway main line traffic flow under the traffic event conditions will significantly improve the dynamic safety control level and risk warning ability of the expressway main line.

Citation Download Citation

Guoqiang Li "Study on dynamic assessment and early warning model of expressway traffic flow risk", Proc. SPIE 12708, 3rd International Conference on Internet of Things and Smart City (IoTSC 2023）, 127082S (14 June 2023); https://doi.org/10.1117/12.2683922

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