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The Severity of Traffic Crashes in Italy: An Explorative Analysis among Different Driving Circumstances

Author

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  • Laura Eboli

    (Department of Civil Engineering, University of Calabria, 87036 Rende, Italy)

  • Carmen Forciniti

    (Department of Civil Engineering, University of Calabria, 87036 Rende, Italy)

Abstract

Analyzing traffic accidents is very important due to their direct impact on the social environment. In the literature, many studies focus on the different aspects that influence traffic accidents, such as human, vehicle, road and environment risk factors. In this paper, we propose a methodology for testing the relationship between road, external environment, driver and vehicle characteristics, and certain circumstances that lead to the traffic crashes. Particularly, we elaborate on logistic regression models for evaluating how these different characteristics impact on crash severity, considering the combination of traffic circumstances that caused the crash. In each combination, a vehicle proceeded regularly, whereas the other vehicle did an incorrect maneuver (the vehicle proceeded: with distracted driving; without maintaining the safety distance; with speeding; by maneuvering to join the circulation flow; against the flow). The present work analyzes data related to road crashes which occurred in Italy during 2016 involving two vehicles. The results show that the variables significantly influencing crash severity are different depending on the combinations of circumstances that cause the crash.

Suggested Citation

  • Laura Eboli & Carmen Forciniti, 2020. "The Severity of Traffic Crashes in Italy: An Explorative Analysis among Different Driving Circumstances," Sustainability, MDPI, vol. 12(3), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:856-:d:312413
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    References listed on IDEAS

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    Cited by:

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    2. Sarah Najm Abdulwahid & Moamin A. Mahmoud & Nazrita Ibrahim & Bilal Bahaa Zaidan & Hussein Ali Ameen, 2022. "Modeling Motorcyclists’ Aggressive Driving Behavior Using Computational and Statistical Analysis of Real-Time Driving Data to Improve Road Safety and Reduce Accidents," IJERPH, MDPI, vol. 19(13), pages 1-20, June.
    3. Jianyu Wang & Huapu Lu & Zhiyuan Sun & Tianshi Wang, 2020. "Exploring Factors Influencing Injury Severity of Vehicle At-Fault Accidents: A Comparative Analysis of Passenger and Freight Vehicles," IJERPH, MDPI, vol. 17(4), pages 1-12, February.
    4. Jiho Yeo & Shin-Hyoung Park, 2021. "Effect of Smartphone Dependency on Smartphone Use While Driving," Sustainability, MDPI, vol. 13(10), pages 1-13, May.
    5. Ying Cheng & Zhen Liu & Li Gao & Yanan Zhao & Tingting Gao, 2022. "Traffic Risk Environment Impact Analysis and Complexity Assessment of Autonomous Vehicles Based on the Potential Field Method," IJERPH, MDPI, vol. 19(16), pages 1-14, August.
    6. Tasneem Miqdady & Juan de Oña, 2020. "Identifying the Factors That Increase the Probability of an Injury or Fatal Traffic Crash in an Urban Context in Jordan," Sustainability, MDPI, vol. 12(18), pages 1-16, September.

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