Macro level Model Development for Safety Assessment of Road Network Structures

Traffic safety is beginning to receive increasing attention at the stage of transportation planning. Although the features of road networks are an essential aspect of transportation planning, studies of the safety effects of network patterns remain limited. In this study, macrolevel safety models were developed to explore the relationship between crash occurrence and several underlying variables, including demographic, land use, and road network variables. Different indices (e.g., the meshedness coefficient and closeness centrality) of network structures were developed to examine the effects of the network structure on safety at the zonal level. In many cases, a large percentage of the crash locations (especially for arterial crashes) was not related to the traffic analysis zones (TAZs) where drivers lived. To link crashes and features properly at the zonal level, crashes of each TAZ were modeled separately for non-state-maintained arterials (i.e., off-system roadways) and state-maintained arterials (i.e., on-system roadways). Several conditional autoregressive Bayesian models that incorporated the spatial correlation of nearby zones were developed. Estimation results showed that crashes occurring on non-state-maintained roads correlated more closely with the zonal network structure and the demographic characteristics inside the TAZ than did crashes occurring on state-maintained arterials; crashes on state-maintained arterials correlated more closely with the traffic and features of the major roads. The categorical variable generated from the meshedness coefficient captured well the nature of the relationship of network patterns to off-system road crashes. The results of this study indicate that both the roadway type and the structure of the road network should be considered when TAZ-level safety models are developed.