IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i3p856-d312413.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/3/856/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/3/856/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Itf, 2019. "Road Safety in European Cities: Performance Indicators and Governance Solutions," International Transport Forum Policy Papers 67, OECD Publishing.
    2. Hou, Qinzhong & Huo, Xiaoyan & Leng, Junqiang & Cheng, Yuxing, 2019. "Examination of driver injury severity in freeway single-vehicle crashes using a mixed logit model with heterogeneity-in-means," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    3. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
    4. Xiong, Yingge & Tobias, Justin L. & Mannering, Fred L., 2014. "The analysis of vehicle crash injury-severity data: A Markov switching approach with road-segment heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 109-128.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feifeng Jiang & Kwok Kit Richard Yuen & Eric Wai Ming Lee & Jun Ma, 2020. "Analysis of Run-Off-Road Accidents by Association Rule Mining and Geographic Information System Techniques on Imbalanced Datasets," Sustainability, MDPI, vol. 12(12), pages 1-32, June.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    2. Dong, Chunjiao & Shao, Chunfu & Clarke, David B. & Nambisan, Shashi S., 2018. "An innovative approach for traffic crash estimation and prediction on accommodating unobserved heterogeneities," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 407-428.
    3. Tong Zhu & Zishuo Zhu & Jie Zhang & Chenxuan Yang, 2021. "Electric Bicyclist Injury Severity during Peak Traffic Periods: A Random-Parameters Approach with Heterogeneity in Means and Variances," IJERPH, MDPI, vol. 18(21), pages 1-19, October.
    4. Yan, Ying & Zhang, Ying & Yang, Xiangli & Hu, Jin & Tang, Jinjun & Guo, Zhongyin, 2020. "Crash prediction based on random effect negative binomial model considering data heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    5. Najaf, Pooya & Thill, Jean-Claude & Zhang, Wenjia & Fields, Milton Greg, 2018. "City-level urban form and traffic safety: A structural equation modeling analysis of direct and indirect effects," Journal of Transport Geography, Elsevier, vol. 69(C), pages 257-270.
    6. Khondoker Billah & Qasim Adegbite & Hatim O. Sharif & Samer Dessouky & Lauren Simcic, 2021. "Analysis of Intersection Traffic Safety in the City of San Antonio, 2013–2017," Sustainability, MDPI, vol. 13(9), pages 1-18, May.
    7. Bo Yang & Yao Wu & Weihua Zhang & Jie Bao, 2020. "Modeling Collision Probability on Freeway: Accounting for Different Types and Severities in Various LOS," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    8. Bae, Bumjoon & Seo, Changbeom, 2022. "Do public-private partnerships help improve road safety? Finding empirical evidence using panel data models," Transport Policy, Elsevier, vol. 126(C), pages 336-342.
    9. Svetlana BAČKALIĆ & Dragan JOVANOVIĆ & Todor BAČKALIĆ & Boško MATOVIĆ & Miloš PLJAKIĆ, 2019. "The Application Of Reliability Reallocation Model In Traffic Safety Analysis On Rural Roads," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 14(1), pages 115-125, April.
    10. Izdebski, Mariusz & Jacyna-Gołda, Ilona & Gołda, Paweł, 2022. "Minimisation of the probability of serious road accidents in the transport of dangerous goods," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    11. Renfei Wu & Xunjia Zheng & Yongneng Xu & Wei Wu & Guopeng Li & Qing Xu & Zhuming Nie, 2019. "Modified Driving Safety Field Based on Trajectory Prediction Model for Pedestrian–Vehicle Collision," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    12. Lv, Jinpeng & Lord, Dominique & Zhang, Yunlong & Chen, Zhi, 2015. "Investigating Peltzman effects in adopting mandatory seat belt laws in the US: Evidence from non-occupant fatalities," Transport Policy, Elsevier, vol. 44(C), pages 58-64.
    13. Ye, Wei & Xu, Yueru & Shi, Xiaomeng & Shiwakoti, Nirajan & Ye, Zhirui & Zheng, Yuan, 2024. "A macroscopic safety indicator for road segment: application of entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 642(C).
    14. Dereli, Mehmet Ali & Erdogan, Saffet, 2017. "A new model for determining the traffic accident black spots using GIS-aided spatial statistical methods," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 106-117.
    15. Maria Luisa Tumminello & Elżbieta Macioszek & Anna Granà, 2024. "Insights into Simulated Smart Mobility on Roundabouts: Achievements, Lessons Learned, and Steps Ahead," Sustainability, MDPI, vol. 16(10), pages 1-33, May.
    16. Ruru Xing & Zimu Li & Xiaoyu Cai & Zepeng Yang & Ningning Zhang & Tao Yang, 2023. "Accident Rate Prediction Model for Urban Expressway Underwater Tunnel," Sustainability, MDPI, vol. 15(13), pages 1-28, July.
    17. Wang, Hwachyi & De Backer, Hans & Lauwers, Dirk & Chang, S.K.Jason, 2019. "A spatio-temporal mapping to assess bicycle collision risks on high-risk areas (Bridges) - A case study from Taipei (Taiwan)," Journal of Transport Geography, Elsevier, vol. 75(C), pages 94-109.
    18. Ulak, Mehmet Baran & Ozguven, Eren Erman & Spainhour, Lisa & Vanli, Omer Arda, 2017. "Spatial investigation of aging-involved crashes: A GIS-based case study in Northwest Florida," Journal of Transport Geography, Elsevier, vol. 58(C), pages 71-91.
    19. Petr Halámek & Radka Matuszková & Michal Radimský, 2021. "Modernisation of Regional Roads Evaluated Using Ex-Post CBA," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    20. Chen, Roger B., 2018. "Models of count with endogenous choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 862-875.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:856-:d:312413. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.