A comprehensive analysis of the relationships between the built environment and traffic safety in the Dutch urban areas. (July 2022)

• Record Type: Journal Article
• Authors: Asadi, Mehrnaz; Ulak, Mehmet Baran; Geurs, Karst T.; Weijermars, Wendy; Schepers, Paul
• Is Part Of: Accident analysis and prevention. Volume 172(2022)
• Publication Date: 2022-07
• Subjects: Traffic safety -- Built-environment -- Land-use design -- Proximity to facilities -- Spatial spillover effects -- Hurdle Negative Binomial model; Accidents -- Prevention -- Periodicals; Accident Prevention -- Periodicals; Accidents -- Prévention -- Périodiques; 363.106
• DOI: 10.1016/j.aap.2022.106683
• Languages: English
• ISSNs: 0001-4575

Abstract

Highlights: Built-environment affects vehicle-bicycle crashes more than vehicle only crashes. Magnitude of built-environment impacts varies based on crash severity. Newly designed urban areas are safer for cyclists and motor-vehicle users. Vehicle-bicycle crashes are more probable in areas with high urbanity level. Abstract: Built-environment factors potentially alleviate or aggravate traffic safety problems in urban areas. This paper aims to investigate the relationships of these factors with vehicle-bicycle and vehicle-vehicle property damage only (PDO) and killed and severe injury (KSI) crashes in urban areas. For this purpose, an area-level analysis using 100x100m 2 cells, along with a Spatial Hurdle Negative Binomial regression model were employed. The study area is composed of a selection of municipalities in the Netherlands-Randstad Area where major land-use developments have occurred since the 1970s. The study was conducted by developing a rich dataset composed of various national and local databases. The findings reveal that built-environment factors and land-use policies have substantial impacts on safety, which cannot be neglected. The factors explaining the land-use density and diversity in the area (e.g., urbanity and function mixing levels), as well as the land-use design characteristics (indicated by average age of the neighborhoods), traffic and road network characteristics, and proximity to different destinations influence the probability, frequency, and severity of crashes in urban areas. Furthermore, low socioeconomic levels are associated with a higher frequency of traffic crashes.