Abstract
Ensuring pedestrian safety is crucial for establishing fair and sustainable transportation systems. However, certain demographics face disproportionately higher risks, necessitating age-appropriate policy and design strategies. This study provides a comprehensive analysis of the relationships between objectively measured road infrastructure attributes and pedestrian accident frequencies involving vulnerable groups in Hunan Province, China. By leveraging detailed historical crash records linked to spatially-explicit infrastructure data, the research team employed advanced count regression modeling techniques, including negative binomial (NB) and zero truncated tail negative binomial (ZTNB) specifications, to systematically evaluate the safety impacts of roadway functional classification, intersection design, traffic controls, alignment geometry, pedestrian segregation, land use context, and traffic volumes. The results revealed that the ZTNB approach, which accounted for the excess zero observations inherent to the crash data, provided statistically superior model fit compared to the standard NB formulation. The ZTNB estimation results offered robust empirical evidence regarding key infrastructure risk factors, highlighting that while higher-order roadways exhibited lower pedestrian accident likelihoods, elements such as multi-leg intersections, lack of traffic controls, curved alignments, and absence of segregated facilities correlated with elevated hazards. Older adults and children are particularly susceptible to accidents on major highways and are more prone to traffic incidents on regular roads as opposed to specialized areas like tunnels and intersections. Importantly, the analysis revealed varying safety impacts among different user groups, underscoring the significance of considering the unique requirements and vulnerabilities of diverse pedestrian populations in transportation planning and design. Overall, the findings offer robust empirical evidence to guide development of tailored interventions that consider the unique capacities and exposures of different pedestrian populations. The age-segmented analyses also contribute transportation equity insights for achieving Vision Zero goals through inclusive infrastructure design.