One step toward lowering traffic accidents is identifying the locations of road accident hotspots and the appropriate assessment technique. This study evaluated the effectiveness of kernel density estimation (KDE) and the weighted severity index (WSI) in locating blackspots using the ArcGIS tool. Finding out accident severity levels is necessary to identify the accident-related blackspots. The formula for the WSI method was applied. This study examines five-year traffic accidents in the Bhopal, Madhya Pradesh, city intersection zone of the roads to envisage the appropriateness for the given technique on the basis of availability, consistency, and type of the data. This study designates five typical road network intersection zones as blackspot sites based on the criterion. This study's general conclusion is that, during the years 2017 to 2019, Govindpura Turning in Bhopal is a highly accident-prone area, and point density estimation is preferable to kernel density estimation for this purpose. Additionally, this study found that between 2015 and 2017, high-traffic accidents in Sukhisewaniya's Balampur Ghati were more likely to occur in intersection zones with a large number of legs. This study suggests that point density estimation be used to investigate high number of traffic accident areas by looking into blackspot locations at the macroscopic level of road networks. Furthermore, it is necessary to evaluate the effectiveness of the designated blackspot site and suggest corrective measures that reduce the number of accidents and their consequences.
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