Comparative methods for identifying hotspots of adverse weather crashes

Identification of road crash Hotspots related to adverse weather is critical in implementing effective measures for reducing road crashes. A reliable hotspot identification method and firm criteria for evaluation are essential for accurately predicting crash risk Hotspots related to adverse weather. These steps will significantly enhance the accuracy of hotspot predictions and improve road safety efforts. This study investigates significant road safety issues related to adverse weather conditions in Jordan by testing hotspot identification methods (HSIDs) for crashes occurring under these conditions. The study applies and compares several hotspot ranking techniques including the Crash rate method (CR), the Crash frequency method (CF), the potential for improvement using predicted crashes (PI), and the Empirical Bayes method (EB), using a detailed dataset of weather-related crashes. The HSID methods are systematically tested using several statistical tests and assessed to determine the reliable approach/es for detecting hazardous sites during adverse weather conditions. The analysis encompasses urban and rural road segments, involving their operational and road characteristics and various crash characteristics. By integrating modern statistical tools, the study provides a detailed assessment of crash-identified Hotspots under adverse weather conditions and highlights major findings. The findings provide significant insights for decision-makers, emphasizing the importance of targeted initiatives and better road safety measures in identifying hotspots. Based on the findings, the study proposes some techniques for improving road safety related to poor weather Given the study's limitations, further and more comprehensive research is recommended to address these limitations and reach more conclusive results. This offers a strong foundation for decision-makers and traffic safety authorities to put into practice strategies to lower crash rates and enhance safety during inclement weather.