Evaluating safety countermeasures at suburban arterial intersections: Addressing unobserved heterogeneity and selection bias

About 40% of road traffic crashes occur at intersections, with suburban arterial intersections facing significant safety challenges due to urban sprawl. Over the past two decades, highways in suburban areas of many Chinese cities, originally designed for medium- and long-distance vehicle travel, now accommodate more short- and medium-distance trips, including pedestrians and cyclists. Discrepancies between original planning characteristics and current usage have led to increased safety risks at suburban arterial intersections. This study evaluates the effectiveness of safety countermeasures implemented at 32 intersections across six suburban arterials in Suzhou, China, which were improved in 2021. To address unobserved heterogeneity and selection bias, a propensity score matching-full Bayes (PSM-FB) method was employed to calculate crash modification factors (CMFs) by balancing the distribution of variables between treatment and control groups. The random effects negative binomial (RE-NB) model was used as the safety performance function (SPF) to account for unobserved heterogeneity among arterials and intersections. Three safety countermeasures were analyzed: physical separation of bicycle lanes, installation of mandatory stop signs for large vehicles at right turns, and removal of obstructions to improve sight distances. Results indicate significant reductions in crashes across all types and severities, with CMFs below 1.0 for all countermeasures. Physical separation of bicycle lanes demonstrated notable effectiveness in reducing bicycle- and pedestrian-related crashes. The PSM-FB method effectively addressed unobserved heterogeneity and selection bias, offering a robust framework for safety evaluation. This study contributes to improving suburban arterial intersection safety and provides methodological insights for future evaluations.