The research on indirect incident detection in expressway under high traffic density

Fuhai Wang; Anran Li; Zijian Wang; Xinpeng Yao; Weichao Hu

doi:10.1117/12.2652752

21 November 2022 The research on indirect incident detection in expressway under high traffic density

Fuhai Wang, Anran Li, Zijian Wang, Xinpeng Yao, Weichao Hu

Proceedings Volume 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022); 123402C (2022) https://doi.org/10.1117/12.2652752
Event: International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 2022, Lanzhou, China

Abstract

With the continuous construction of expressways in China, the timely process of traffic incidents has been increasingly valued to avoid heavy traffic and secondary incidents. To timely eliminate the terrible influence of incidents, the indirect incident detection method is designed and presented based on the actual data of the segment from the Lingdian interchange to the Tangwang interchange hub of the Jinan-Guangzhou expressway in this paper. Firstly, the existing data from diverse detection systems are collected and integrated into a unified format. Then, an actual-data-based simulation experiment is achieved to offer the required information to the indirect incident detection method through VISSIM. On this basis, a series of parameters are constructed to identify the mutation of traffic operation from multi-dimension. Finally, the indirect incident detection method is trained to recognize the mutation of traffic and classify the normal scene and incident scene with LightGBM. Compared to KNN, RF, and SVM, the LightGBM has an excellent performance on incident identification, with a 98.6% accuracy, a 100% precision, an 88.9% recall, and a 94.1% F1 score.

Citation Download Citation

Fuhai Wang, Anran Li, Zijian Wang, Xinpeng Yao, and Weichao Hu "The research on indirect incident detection in expressway under high traffic density", Proc. SPIE 12340, International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), 123402C (21 November 2022); https://doi.org/10.1117/12.2652752

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KEYWORDS

Roads

Detection and tracking algorithms

Sensors

Data integration

Intelligence systems

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Data modeling

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