In recent years, with the rapid development of road traffic in China, the problem of road traffic safety has become increasingly prominent, especially the illegal behavior of vehicles not using high beam lights according to regulations when driving at night, which has gradually become the main cause of traffic accidents at night. According to statistics, about 43% of nighttime traffic accidents are related to the abuse of high beam lights. The main reasons are that the driver is not clear about the provisions of the high beam lamp, not familiar with the operation, and deliberately turns on the light for a long time. The problem has affected the normal and stable social order. Therefore, it is of great significance to effectively prevent the abuse of high beam lights by vehicles at night for promoting traffic safety and social order at night. This paper takes the abuse of high beam lights by vehicles at night as the research object, analyzes the problems of night traffic in detail in combination with various conditions of the night road, and studies and proposes a new intelligent warning system optimization scheme to prevent the abuse of high beam lights by road vehicles at night. Through research and creation of high beam data collection algorithm processing, the intelligent traffic system for driving at night is established to reduce the incidence of traffic accidents and ensure traffic safety.


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    Titel :

    Study on the optimization of intelligent transportation system for preventing the abuse of high beam


    Beteiligte:
    Kong, Xiangjie (Herausgeber:in) / Falcone, Francisco (Herausgeber:in) / Yin, Zehao (Autor:in) / Wang, Wenjie (Autor:in) / Zhang, Xinyu (Autor:in) / Sui, Zixin (Autor:in) / Li, Weichuang (Autor:in) / Jia, Yiwei (Autor:in) / Wang, Zhiguo (Autor:in) / Zhang, Shaojie (Autor:in)

    Kongress:

    3rd International Conference on Internet of Things and Smart City (IoTSC 2023) ; 2023 ; Chongqing, China


    Erschienen in:

    Proc. SPIE ; 12708


    Erscheinungsdatum :

    2023-06-14





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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