IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i16p9840-d883968.html
   My bibliography  Save this article

Prediction of Crash Severity as a Way of Road Safety Improvement: The Case of Saint Petersburg, Russia

Author

Listed:
  • Maria Rodionova

    (Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia)

  • Angi Skhvediani

    (Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia)

  • Tatiana Kudryavtseva

    (Graduate School of Industrial Economics, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia)

Abstract

This article investigates factors that explain road crash severity levels in Saint Petersburg, Russia, during the 2015–2021 period. The research takes into account factors such as lighting conditions, weather conditions, infrastructure factors, human factors, accident types, and vehicle category and color to assess their influence on crash severity. The most influential accident type is run-off-road crashes, which are associated with an 11.2% increase in fatal accidents. The biggest reason for the increase in fatal accidents due to road infrastructure conditions is road barrier shortcomings (2.8%). Road infrastructure conditions, such as a lack of road lighting, have a significant effect on fatal outcomes, increasing them by 12.6%, and this is the most influential factor in the analysis. The obtained results may serve as a basis for Saint Petersburg authorities to develop new road safety policies.

Suggested Citation

  • Maria Rodionova & Angi Skhvediani & Tatiana Kudryavtseva, 2022. "Prediction of Crash Severity as a Way of Road Safety Improvement: The Case of Saint Petersburg, Russia," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:9840-:d:883968
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/16/9840/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/16/9840/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2021. "Analysis of Pedestrian–Motor Vehicle Crashes in San Antonio, Texas," Sustainability, MDPI, vol. 13(12), pages 1-23, June.
    2. Aziemah Azhar & Noratiqah Mohd Ariff & Mohd Aftar Abu Bakar & Azzuhana Roslan, 2022. "Classification of Driver Injury Severity for Accidents Involving Heavy Vehicles with Decision Tree and Random Forest," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
    3. Giovanny Pillajo-Quijia & Blanca Arenas-Ramírez & Camino González-Fernández & Francisco Aparicio-Izquierdo, 2020. "Influential Factors on Injury Severity for Drivers of Light Trucks and Vans with Machine Learning Methods," Sustainability, MDPI, vol. 12(4), pages 1-28, February.
    4. Federico Orsini & Mariaelena Tagliabue & Giulia De Cet & Massimiliano Gastaldi & Riccardo Rossi, 2021. "Highway Deceleration Lane Safety: Effects of Real-Time Coaching Programs on Driving Behavior," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    Full references (including those not matched with items on IDEAS)

    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. Amini, Mostafa & Bagheri, Ali & Delen, Dursun, 2022. "Discovering injury severity risk factors in automobile crashes: A hybrid explainable AI framework for decision support," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Yong Fang & Jiayi Zhou & Hua Hu & Yanxi Hao & Dianliang Xiao & Shaojie Li, 2022. "Combination Layout of Traffic Signs and Markings of Expressway Tunnel Entrance Sections: A Driving Simulator Study," Sustainability, MDPI, vol. 14(6), pages 1-13, March.
    3. Xin Tian & Mengmeng Shi & Mengyu Shao & Binghong Pan, 2023. "Calculation Method of Deceleration Lane Length and Slope Based on Reliability Theory," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    4. Almudena Sanjurjo-de-No & Ana María Pérez-Zuriaga & Alfredo García, 2023. "Factors Influencing the Pedestrian Injury Severity of Micromobility Crashes," Sustainability, MDPI, vol. 15(19), pages 1-17, September.
    5. Jaeheon Choi & Kyuil Lee & Hyunmyung Kim & Sunghi An & Daisik Nam, 2020. "Classification of Inter-Urban Highway Drivers’ Resting Behavior for Advanced Driver-Assistance System Technologies using Vehicle Trajectory Data from Car Navigation Systems," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    6. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2023. "Bivariate-Logit-Based Severity Analysis for Motorcycle Crashes in Texas, 2017–2021," Sustainability, MDPI, vol. 15(13), pages 1-26, June.
    7. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2022. "How Gender Affects Motor Vehicle Crashes: A Case Study from San Antonio, Texas," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    8. Fabricio Esteban Espinoza-Molina & Christian Fernando Ojeda-Romero & Henry David Zumba-Paucar & Giovanny Pillajo-Quijia & Blanca Arenas-Ramírez & Francisco Aparicio-Izquierdo, 2021. "Road Safety as a Public Health Problem: Case of Ecuador in the Period 2000–2019," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    9. Lili Zheng & Xinyu He & Tongqiang Ding & Yanlin Li & Zhengfeng Xiao, 2022. "Analysis of the Accident Propensity of Chinese Bus Drivers: The Influence of Poor Driving Records and Demographic Factors," Mathematics, MDPI, vol. 10(22), pages 1-20, November.
    10. Khondoker Billah & Hatim O. Sharif & Samer Dessouky, 2021. "Analysis of Bicycle-Motor Vehicle Crashes in San Antonio, Texas," IJERPH, MDPI, vol. 18(17), pages 1-19, September.

    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:14:y:2022:i:16:p:9840-:d:883968. 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.