Detection of Crash Black Spots for Indian Traffic Conditions Using MoRTH-Based Sliding Window Method

Road safety is a global concern, with traffic crashes posing significant threats to human life and well-being. This study conducted an exploratory analysis of crash data, obtained from the District Crime Records Bureau Kollam, to identify factors contributing to crashes on National Highway 66 (NH 66) in Kollam district of Kerala in India and employed a dynamic method, namely, the Sliding Window Method (SWM) for black spot determination. The conventional method of black spot determination uses the definition by The Ministry of Road Transport and Highways (MoRTH) where a road crash black spot on National Highways is defined as a road stretch of about 500 m where either five accidents (involving fatalities/grievous injuries) occurred in the last three calendar years or ten fatalities took place during the same period. This method divides the road stretch into static 500 m segments, thereby missing out on the black spot that may be hidden within these static segments. Thus, this study aims to compare the conventional method of black spot determination by MoRTH with a sliding window method based on MoRTH guidelines, thereby evaluating the efficiency of the sliding window method to capture all potential black spots in the selected study stretch. The study results revealed that the sliding window method identified 162 black spots compared to 87 identified by the conventional method, showcasing the enhanced sensitivity of SWM.