Investigating Factors Contributing to Urban Traffic Incident Risk Using High-Resolution Heterogeneous Data - Dongpeng Zhu; Yuzhi Zhang; Dilin Wen; Linchao Li (Journal of Advanced Transportation)
Urban traffic incidents are among the leading causes of death, injury, and traffic congestion in metropolises worldwide. This paper aims to investigate the effects of social demography, road networks, land use, and public transportation facilities on the traffic incident risk in Shenzhen, China. High-resolution heterogeneous data are collected for 4207 grids which are used as the basic geographic units. The traffic incident risks of grids are divided into four levels according to the number of incidents. A generalized ordered logit (GOL) model is developed to explore the contributions and elasticity of the variables. The results show that the effect of the significant variables on various thresholds is different. Employment density has a more significant impact on the risk level than population density. Compared to nonworking days, trips during working days are more relevant to the traffic incident risk. Road network variables such as the length of various road types and intersections are positively correlated with the incident risk. For the land use variables, most of them are significant influencing variables. The findings of the paper can provide some suggestions for safety management policies of arterial intersections, critical infrastructures, and future urban land use planning.