  With the rapid changes in land use development along suburban arterials in
Shanghai, there is also a corresponding increase in traffic demand along these
arterials. With a preference toward increased accessibility and efficiency,
these arterials have been installed with an increased number of signalized
intersections and accesses to serve local traffic needs. The absence of a
defined functional hierarchy along the road network, together with the
non-uniform installation of signals and accesses tends to deteriorate arterial
safety. Previous studies on arterial safety have generally been based on a
single type of road entity (either intersection or roadway segment). These
studies only analyzed partial safety impacts of signal spacing and access
density, as these factors would significantly influence the safety performance
of both intersections and roadway segments. Macro level safety modeling was
usually applied to investigate the relationship between the zonal crash
frequencies and demographics, road network features and traffic
characteristics. In this study, a new modeling strategy was proposed to analyze
the safety impacts of roadway network features (i.e., road network patterns,
signal spacing and access density) of arterials by applying a macro level
safety modeling technique. Bayesian Conditional Autoregressive models were
developed for arterials covering 173 Traffic Analysis Zones in the suburban
area in Shanghai. The results identified that the road network pattern with
collector roads parallel to the arterials was shown to be associated with fewer
crashes than those without parallel collectors. Higher signal density and
access density also tended to increase crash frequencies on arterials.
