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Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Hangzhou, China

Research Article

Research on Traffic Safety Risk Identification of Highway Tunnels Based on Apriori

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  • @INPROCEEDINGS{10.4108/eai.19-5-2023.2334404,
        author={Mimi  Zhang},
        title={Research on Traffic Safety Risk Identification of Highway Tunnels Based on Apriori},
        proceedings={Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19--21, 2023, Hangzhou, China},
        publisher={EAI},
        proceedings_a={ICBBEM},
        year={2023},
        month={7},
        keywords={tunnel; association rule mining algorithm; traffic safety risk identification},
        doi={10.4108/eai.19-5-2023.2334404}
    }
    
  • Mimi Zhang
    Year: 2023
    Research on Traffic Safety Risk Identification of Highway Tunnels Based on Apriori
    ICBBEM
    EAI
    DOI: 10.4108/eai.19-5-2023.2334404
Mimi Zhang1,*
  • 1: Nanchang Institute of Technology
*Contact email: 1779262717@qq.com

Abstract

The traffic accident data onto highway tunnels are statistically analyzed. The improved Apriori algorithm is applied to extract the frequent item set and set the support degree threshold. And the association rule sets of different types of traffic accident characteristic attribute are obtained, the main risk sources and correlation relationships affecting the traffic safety of highway tunnels are found out. The technical support and rationalized prevention advice are provided to improve the safety management of highway tunnel operation, strengthen the identification of accident risks in tunnels, and reduce the losses caused by tunnel accidents to traffic efficiency and personal and property safety.

Keywords
tunnel; association rule mining algorithm; traffic safety risk identification
Published
2023-07-24
Publisher
EAI
http://dx.doi.org/10.4108/eai.19-5-2023.2334404
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