Exploring the associations between pavement conditions and pedestrian and cyclist crashes

Pavement condition indicators, alongside other factors, are increasingly recognised as important correlates of traffic crash risk, yet their associations with Vulnerable Road User (VRU) crash frequencies are inadequately explored. This study investigates how pavement conditions are associated with pedestrian and cyclist crashes while controlling for infrastructure, travel, sociodemographic, and land-use factors. Negative Binomial (NB), Poisson inverse Gaussian (PIG), and Bell regression models are estimated, using data aggregated to Traffic Analysis Zones (TAZs) in Victoria, Australia. Modelling results show that higher proportions of road segments with good surface texture and good roughness conditions are associated with significantly fewer pedestrian crashes across all three models. Similarly, a greater proportion of road segments with good surface texture is associated with fewer cyclist crashes consistently across all three models. The results also confirm the associations between VRU crashes and vehicle kilometres travelled, population, public transport and cycling mode shares, signalised intersections, roundabouts, public transport stops, and commercial land use. Overall, this study provides new empirical evidence of significant associations between pavement conditions, particularly surface texture and roughness, and VRU crashes. Transport and road safety agencies should consider pavement management as an integral part of VRU safety strategies.