Built environment factors in explaining the automobile-involved bicycle crash frequencies: A spatial statistic approach

Abstract

The objective of this study is to understand the relationship between built environment factors and bicycle crashes with motor vehicles involved in Seattle. The research method employed is a Poisson lognormal random effects model using hierarchal Bayesian estimation. The Traffic Analysis Zone (TAZ) is selected as the unit of analysis to quantify the built environment factors. The assembled dataset provides a rich source of variables, including road network, street elements, traffic controls, travel demand, land use, and socio-demographics. The research questions are twofold: how are the built environment factors associated with the bicycle crashes, and are the TAZ-based bicycle crashes spatially correlated? The findings of this study are: (1) safety improvements should focus on places with more mixed land use; (2) off-arterial bicycle routes are safer than on-arterial bicycle routes; (3) TAZ-based bicycle crashes are spatially correlated; (4) TAZs with more road signals and street parking signs are likely to have more bicycle crashes; and (5) TAZs with more automobile trips have more bicycle crashes. For policy implications, the results suggest that the local authorities should lower the driving speed limits, regulate cycling and driving behaviors in areas with mixed land use, and separate bike lanes from road traffic.