Urban road intersections are the key nodes of urban road network with a mass of traffic flow confliction, which often result in traffic accidents. Therefore, automated conflict detection is crucial for traffic safety analysis. This paper proposes a method to extract traffic conflicts by using deep learning based trajectory detection. The traffic video data is collected by unmanned aircraft in a road intersection in Xi’an, i.e., an ancient city in China. Then, YOLOv5-DeepSORT is employed to extract the vehicle trajectories. Comparing the situation and velocity of vehicles in each time slice, we put forward a method of automatic calculation and extraction of traffic conflict indicator. Moreover, a visualized conflict areas are shown in graphs, which is helpful for the safety analysis of urban road intersections.


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    Title :

    Extracting Traffic Conflict at Urban Intersection Using Deep Learning Trajectory Detection


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Fu, Wenxing (editor) / Gu, Mancang (editor) / Niu, Yifeng (editor) / Zhang, Yunxing (author) / Liu, Lili (author) / Zhu, Tong (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2022 ; Xi'an, China September 23, 2022 - September 25, 2022



    Publication date :

    2023-03-10


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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