ABSTRACT: Regional traffic safety has been a public concern for many metropolitan areas, and it is urgent to turn this situation around by using an appropriate traffic safety analysis and crash hotspot identification method. Existing studies mainly focus on the effects of engineering-related indicators on regional crashes and violations, neglecting the traffic police enforcement-related factors. Meanwhile, the relationship between crashes and violations is insufficiently recognized. To address these gaps, this study selected Suzhou, a rapidly developing Chinese city, and collected socio-economic indicators, road features, land use intensity, facility data, and police enforcement information as independent variables. A Bayesian bivariate negative binomial spatial conditional autoregressive (BNB-CAR) model was developed to capture the association between crashes and violations, as well as their contributing factors. Results showed that (1) there existed a significantly correlated effect between crashes and violations; (2) engineering-related indicators had similar effects on crashes and violations, while some police enforcement-related factors were dual-effective. Based on the model results, this study used the potential for safety improvement (PSI) method to identify the hazardous areas of the 115 towns in Suzhou. It was observed that (1) the spatial distribution of crashes indicated the spatial correlations among the towns; (2) the fringe areas suffered higher crash risks than the downtown areas. Several engineering and enforcement countermeasures were provided for urban planning departments and traffic police to enhance their work effectiveness. Additionally, decision makers and administrators will benefit from this study to improve daily traffic safety management.
Yingying Pei, Xuesong Wang*, Mingjie Feng, Zhixing Zhu, Fang Liu, Zhongyang Qie, Paul P. Jovanis. Macro-Level Safety Analysis of Crashes and Violations: Influencing Factors and Crash Hotspots. Transportation Research Board 100th Annual Meeting, Washington D.C., USA, 2021. 1.25-29.