كاميار صابري

The study of accident-prone areas in Iran faces numerous challenges. The lack of systematic planning to identify an‎d prioritize these areas, coupled with the absence of a comprehensive database documenting high-risk zones, has delayed corrective actions. This research aimed to identify an‎d prioritize accident-prone areas on the Arak-Salafchegan corridor an‎d propose corrective measures with an economic-safety approach. Accident data from December 2022 to January 2024 were collected from the Road Maintenance an‎d Transportation Organization an‎d analyzed by integrating meteorological an‎d environmental lighting data. The methodology included spatiotemporal analysis, Bayesian modeling, an‎d the TOPSIS method for multi-criteria eva‎luation. Results revealed that the average speed on the corridor was 80 km/h, yet 350 daily speeding violations were recorded. Additionally, 307 accidents occurred during this period, with 67 injuries an‎d 24 fatalities concentrated in the evening hours. Spatial analysis, by dividing the corridor into 300-meter segments, identified 15 high-risk points. Bayesian modeling showed factors such as intersections within 200 meters (coefficient: 1.78), residential areas (coefficient: 0.55), an‎d longitudinal slope (coefficient: 0.33) had the highest impact on accident risk. Based on the composite accident index (weight: 9 for fatalities, 3 for injuries), Segment 9 at kilometer 45, with 8 fatalities an‎d 31 injuries, was identified as the most hazardous. Corrective costs for this segment included guardrail installation (540 million Tomans) an‎d warning lights (15 million Tomans). Final prioritization using TOPSIS an‎d weighted criteria indicated Segment 9 (score: 0.506) had the highest priority, followed by Segments 15 (kilometer 78, score: 0.465) an‎d 1-2 (Hajjiabad Industrial Complex entrance, score: 0.458). The total cost of corrective measures for all 15 points was estimated at 28 billion Tomans. Numerical results showed 30% of accidents occurred in June an‎d September, 60% were caused by inattention, an‎d 41% of fatalities resulted from rollovers. Proposed solutions include guardrail installation, geometric redesign of curves, an‎d smart speed control systems. By integrating quantitative analysis an‎d economic criteria, this study provides a scientific framework for optimizing safety management on critical corridors.

تصادفات جاده‌اي، نقاط پرحادثه، ايمني، پيش‌بيني تصادفات

Road accidents, High-accident zones, Safety, Accident prediction, Bayesian modeling

kamyar saberi

ameri-mojaradi