Long-distance passenger lines exceeding 800 kilometers are a crucial component of highway passenger transport. This paper analyzes the causes of traffic accidents on long-distance passenger routes exceeding 800 kilometers from 2014 to 2020. This paper conducts a causal analysis and researches accident-prone scenarios for long-distance passenger lines exceeding 800 km. It selects key characteristics to establish an index system based on human factors, road conditions, and the environment. This paper analyzes the characteristics of humans, roads, and the environment in the traffic system when accidents occur. The Decision Tree model is utilized to investigate the internal relationships among key factors in accident scenarios, such as operating time, human factors, weather, quarter, accident region, holidays, spring transportation, road alignment, and road condition. The results show that the run time, human factors, and weather conditions are important influencing factors for accidents on long-distance passenger lines over 800 km. They have a coupling relationship with factors such as quarter, accident region, road alignment, and road condition. Holidays, spring transportation, highway technical grade, and highway administrative grade are not the important factors affecting the occurrence of accidents on long-distance passenger lines over 800 km. This paper provides a theoretical basis for reducing the potential for accidents and promoting safety within enterprises operating long-distance passenger lines over 800 km. In the future, road transport management departments and road transport enterprises should strengthen safety management, standardize drivers' safe driving behavior, and promote defensive driving knowledge in accident-prone situations.


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    Title :

    Study on Accident Characteristics and Scenarios of Long-distance Passenger Lines over 800 Kilometers


    Contributors:
    Chang Liu (author) / Hongwen Xia (author) / Xingkai Meng (author) / Xueran Wang (author) / Wenhui Luo (author) / Chuna Wu (author)


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




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