Determinants of Pedestrian–Vehicle Crash Severity: Case of Saint Petersburg, Russia

This article investigates factors that explain pedestrian injury severity levels in Saint Petersburg, Russia during the 2015–2021 period. The research takes into account such factors as weather conditions, infrastructure factors, human factors, and lighting conditions to assess their influence on pedestrian injury severity in pedestrian–vehicle crashes. The most influential factors are lighting conditions, particularly the lack of lighting when it is dark, which are associated with a 14.9% increase in fatal accidents. The greatest impact on the increase of fatal accidents due to road infrastructure conditions relates to road barrier shortcomings (4.7%). Such infrastructure road conditions as restraint system for pedestrians and horizontal markings also have a significant effect on fatal outcomes, increasing them by 1.4% and 0.7%, respectively. The obtained results may serve as a basis for St. Petersburg authorities to develop new road safety policies.

Infrastructure factors; Ordered probit; Pedestrian–vehicle crashes; Road accident; Severity modeling

Currently, one of the main global objectives is to reduce road traffic deaths and injuries by 50% by 2030. A vast number of people are killed each year as a result of road traffic crashes. Millions more suffer non-fatal injuries, including lifelong disability. According to the World Health Organization (2018), the lives of approximately 1.35 million people are cut short every year because of a road traffic crash. Between 20 and 50 million more people suffer non-fatal injuries, with many incurring a disability as a result of their injury. Road traffic injuries cause considerable economic losses for victims, for their families, and for nations. These losses are primarily in the form of treatment costs and reduced or lost productivity.

The paper considers data on road accidents in Saint Petersburg, Russia to determine the causes of crashes, which will enable preventive measures to be identified. According to the Road Safety Strategy of the Russian Federation for 2018–2024, the social risk—that is, the number of deaths due to road accidents per 100,000 people—should be reduced to four. The “Safe and high-quality roads” national strategy enshrines “the pursuit of zero mortality”, and the government aim is for there to be no fatal accidents by 2030. To that end, the analysis of road crash data will facilitate the implementation of sufficient measures to improve the existing situation. 

        Here, we consider road safety improvement and the creation of recommendations to reduce severe consequences of road crashes. Possible conditions that affect the level of road safety have been mentioned in numerous studies (Chen et al., 2016; Chen et al., 2020; Ghandour et al., 2020). Some studies present an analysis of the influence of various factors, such as weather conditions, time of day, and the gender of those involved, on the frequency of accidents (Anastasopoulos et al., 2012). Other studies categorize accidents according to severity and give recommendations to reduce severity and fatalities (Ma et al., 2008; Barua et al., 2016; Dong et al., 2016; Zeng et al., 2017). Oftentimes, studies on the conditions that lead to road accidents only look at one type of accident (Nashad et al., 2016; Billah et al., 2021) or the frequency of the occurrence of accidents by type (Mothafer et al., 2016; Cheng et al., 2017; Wang et al., 2017). Some studies also explore factors related to the driver behavior (Wedagama and Wishart, 2018).

Every year, more studies on this topic appear for certain sections of roads and territories, and both the overall situation in the country and reducing the sample to cities are considered. The circumstances mentioned substantiate the relevance of the paper. 

    In this paper, we analyzed accident data in St. Petersburg for the period 2015–2021 consisting of 13,888 observations. We examined different road conditions, weather, severity level, and pedestrians and their exposure vis-à-vis the frequency of data occurrence. We identified an interesting trend, which is that some conditions that do not cause a greater number of accidents can be the cause of a greater number of fatal accidents. We obtained and analyzed some statistical data that can be used in further regression modelling. The main contribution of the paper is the provision of an ordered probit regression analysis to evaluate the impact of observed factors on the severity level of accident outcomes.

        The study results allow us to conclude the following. The most severe accident outcomes in St. Petersburg are the result of vehicle–pedestrian accidents. These account for 13,888 incidents, 5% of which are fatal and about 40% of which result in serious injuries. This fact allowed us to examine this type of accident and the impact of road conditions at the moment of accident occurrence in more detail.

      The main results of the research are: (1) The greatest impact on fatal and severe outcomes was caused by lighting factors, that is, the lack of lighting when it is dark (14.9% and 15.8%, respectively) and illumination when it is dark is off (8.4% and 12.8%, respectively); (2) Precipitation has a significant effect on severity level, causing a 4.3% and 1.7% increase in the probability of severe and fatal outcomes, respectively, and a 5.9% decrease in the probability of slight injuries; (3) Of the top seven road infrastructure shortcomings in St. Petersburg, only road barriers, pedestrian restraint systems, and horizontal markings have a significant effect on changing the severity of road accidents; (4) The more people involved in accidents, the greater the probability of more severe injuries; and (5) Female pedestrians and drivers increase the probability of slight outcomes compared to male pedestrians and drivers, who are associated with an increase in severe and fatal outcomes.

   The research is funded by the Ministry of Science and Higher Education of the Russian Federation as part of World-class Research Center program: Advanced Digital Technologies (contract No. 075-15-2020-934 dated 17.11.2020).

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