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

Maria Rodionova (), Angi Skhvediani and Tatiana Kudryavtseva
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Maria Rodionova: 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

Sustainability, 2022, vol. 14, issue 16, 1-20

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.

Keywords: road safety; crash severity; road condition; ordered probit model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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