A Data-Driven Framework for Scenario-Based Safety Service Patrol Route Prioritization Using Historical Crash Data

Abstract

Safety Service Patrols (SSPs) are highway assistance programs that provide rapid response to crashes, disabled vehicles, and other incidents, helping to reduce congestion and improve roadway safety. Effective SSP coverage planning is important because timely deployment can facilitate quicker incident clearance and reduce the potential for secondary crashes. However, current SSP operations often rely on fixed patrol routes, which may not fully reflect where crash concentrations vary across time, weather, lighting, and roadway surface conditions. This study develops a data-driven framework to identify candidate priority SSP routes using historical crash records. Major interstate corridors in New Jersey, US, within the SSP coverage area were divided into uniform 1-mile roadway segments, and crashes were matched to segments using spatial proximity, roadway name, road system classification, and travel direction. Segment-level crash frequencies were then evaluated under 1152 scenario combinations defined by time of day, day of week, season, surface condition, weather condition, and lighting condition. Each corridor was represented as a directed graph, and feasible direction-specific routes were ranked based on cumulative crash frequency. The results show that crash concentration is spatially clustered, direction-dependent, and sensitive to operational conditions. Some candidate routes remained stable across scenarios, while others shifted with changes in weather, lighting, surface condition, and temporal period. Validation of the proposed route identification framework using recent crash data produced route overlap scores (ROS) of approximately 74 to 95 percent, indicating that many historically identified high-crash routes remained spatially consistent in the validation period. The framework provides a practical planning tool for SSP route reassessment, shift-level planning, and scenario-based patrol prioritization within existing service areas.