This study addresses critical challenges in urban road network safety management—specifically, the inefficiency of manual hazard screening and its heavy reliance on empirical judgment. We propose a screening and prioritization method for urban road hazard points, facilitating a paradigm shift from reactive, post-incident mitigation to proactive, comprehensive pre-evaluation. This framework provides an evidence-based foundation for prioritizing hazard remediation according to severity and urgency. First, a three-layer screening framework is established, comprising 1) a road network topology layer, 2) a traffic operation layer, and 3) a conflict identification layer. Guided by the principles of accessibility, representability, and computability, this architecture systematically integrates 10 indicators across these layers. Second, leveraging both static physical infrastructure data and dynamic traffic operational data from urban roads, we develop classification and grading rules for hazard identification. Each indicator is categorized into a four rating scale (0-3 points) reflecting hazard levels. Subsequently, a scenario-based weighted summation of these indicators facilitates a graded screening and prioritization of urban road networks. High-priority locations and segments for safety interventions are identified using predetermined percentile thresholds. For the top-tier hazard points, management suggestions can be formulated based on their performance in the conflict identification indicator set. Finally, high-priority intersections are pinpointed through a large-scale case study encompassing 18 major Chinese cities. The analysis reveals recurrent hazard patterns and typical scenarios, thereby offering targeted support for addressing critical issues at urban road junctions.
Liu et al. (Thu,) studied this question.