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Identifying Factors that Influence the Patterns of Road Crashes Using Association Rules: A case Study from Wisconsin, United States

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Listed:
  • Shuai Yu

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Yuanhua Jia

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Dongye Sun

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

Road traffic injury is currently the leading cause of death among children and young adults aged 5–29 years all over the world. Measures must be taken to avoid accidents and promote the sustainability of road safety. The current study aimed to identify risk factors that are significantly associated with the severity in crash accidents; therefore, traffic crashes could be reduced, and the sustainable safety level of roadways could be improved. The Apriori algorithm is carried out to mine the significant association rules between the severity of the crash accidents and the factors influencing the occurrence of crash accidents. Compared to previous studies, the current study included the variables more comprehensively, including environment, management, and the state of drivers and vehicles. The data for the current study comes from the Wisconsin Transportation crash database that contains information on all reported crashes in Wisconsin in the year 2016. The results indicate that male drivers aged 16–29 are more inclined to be involved in crashes on roadways with no physical separation. Additionally, fatal crashes are more likely to occur in towns while property damage crashes are more likely to occur in the city. The findings can help government to make efficient policies on road safety improvement.

Suggested Citation

  • Shuai Yu & Yuanhua Jia & Dongye Sun, 2019. "Identifying Factors that Influence the Patterns of Road Crashes Using Association Rules: A case Study from Wisconsin, United States," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:7:p:1925-:d:218805
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    References listed on IDEAS

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    Cited by:

    1. Shanshan Wei & Xiaoyan Shen & Minhua Shao & Lijun Sun, 2021. "Applying Data Mining Approaches for Analyzing Hazardous Materials Transportation Accidents on Different Types of Roads," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    2. Junxiang Zhang & Bo Yu & Yuren Chen & You Kong & Jianqiang Gao, 2022. "Comparative Analysis of Influencing Factors on Crash Severity between Super Multi-Lane and Traditional Multi-Lane Freeways Considering Spatial Heterogeneity," IJERPH, MDPI, vol. 19(19), pages 1-15, October.
    3. Batara Surya & Hamsina Hamsina & Ridwan Ridwan & Baharuddin Baharuddin & Firman Menne & Andi Tenri Fitriyah & Emil Salim Rasyidi, 2020. "The Complexity of Space Utilization and Environmental Pollution Control in the Main Corridor of Makassar City, South Sulawesi, Indonesia," Sustainability, MDPI, vol. 12(21), pages 1-41, November.
    4. Shuai Yu & Bin Li & Dongmei Liu, 2023. "Exploring the Public Health of Travel Behaviors in High-Speed Railway Environment during the COVID-19 Pandemic from the Perspective of Trip Chain: A Case Study of Beijing–Tianjin–Hebei Urban Agglomera," IJERPH, MDPI, vol. 20(2), pages 1-22, January.
    5. Danish Farooq & Sarbast Moslem & Szabolcs Duleba, 2019. "Evaluation of Driver Behavior Criteria for Evolution of Sustainable Traffic Safety," Sustainability, MDPI, vol. 11(11), pages 1-15, June.

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