Identifying crash risk factors and high risk locations on an interstate network

Abstract

Highway safety improvement projects are identified by using either (i) a site-specific or (ii) a systemic approach. In the site-specific approach, locations for improvements are ranked according to different performance measures such as critical crash rate, expected crash rate or equivalent property damage only. Alternatively, in the systemic approach, roadway characteristics such as number of lanes, shoulder width, etc. are flagged as a ‘risk’ (or ‘preventative’) feature that increases (decreases) the risk of negative outcomes. Using the Highway Safety Information System database, we seek to merge the two approaches by, first, identifying roadway factors associated with an increased occurrence of car crashes (features we call ‘risk factors’) and, subsequently, identifying roadway segments with a higher crash risk. Specifically, we model the locations of crashes as a realization from a spatial point process. We then parameterize the associated intensity surface of this spatial point process as the sum of a regression on roadway characteristics and spatially correlated error terms. Thus, through the regression piece, we identify hazardous roadway features and through the spatially correlated error terms, we identify locations of high risk.

Driving simulator for evaluating the effects of road geometric design on driver behavior

“…A traditional approach in road safety is to identify risk factors that contribute to the frequency or severity of crashes (De Oña, López, Mujalli, & Calvo, 2013;Dingus et al, 2016;Gibson, Heaton, & Tass, 2018;Papadimitriou et al, 2019;Papadimitriou & Theofilatos, 2017;Zhang, Yau, & Chen, 2013). Many distinct agents play a role in crash occurrence and crash outcome, simultaneously.…”

Identification and Prioritization Techniques Applied to Urban Accident-Prone Locations: A Scoping Review

“…Investigations have focused on behavioral factors (Arun et al, 2021;Dingus et al, 2016), road conflicts (Ang et al, 2017;Budhkar and Maurya, 2017), road infrastructure (Arun et al, 2021;Daniels et al, 2019;Gibson et al, 2017), operational conditions (Roshandel et al, 2015), real-time traffic conditions (Gu et al, 2016;You et al, 2017), accident prediction (Wenqi et al, 2017), and weather conditions (Ahmed et al, 2018;Kopelias et al, 2007).…”

“…The goal is to implement improvements that may involve human behavior, road infrastructure, and/or vehicular engineering (Roshandel et al, 2015). Although accidents have different causes and significant effort is required to identify evidence of associations between accidents and contributing factors, site-specific identification can support projects to improve road safety in places with a high incidence of accidents, despite the different contributing factors (Gibson et al, 2017).…”

“…RTAs may have different causes or causal arrangements, their persistent occurrence at particular locations can reflect underlying characteristics of these sites, making it important to be able to identify such places that may be more prone to accidents (Gibson et al, 2017). The identification of accident-prone locations (APLs) constitutes a first-order analysis aimed at identifying candidate locations for traffic safety measures, mapping critical points, and mitigating harmful effects (Høye and Hesjevoll, 2020).…”