Authors:Â Vibhav.H. V , L. Durga Prashanth , Varun. R. GÂ
Abstract:Â The developments in the domain of transportation have led to a steep rise in economic losses and human losses due to road traffic accidents (RTAs). Identification of such RTA blackspots is considered vital for the effective and efficient utilization of resources to enhance traffic safety features of a road network. The identification of blackspots is not a new concept and has been in practice for a while. Despite the extensive work done in the field, there is an extreme scarcity of studies dedicated to the identification of blackspots exclusively for two-wheelers. In the present study, general accident blackspots and exclusive two-wheeler blackspots are identified on five different stretches in and around the city of Bengaluru, Karnataka. The five stretches under study belong to four major categories of roadways. Three years of accident data (2017-2019) is obtained from the police stations and the features of the road are recorded through on-field surveys. The accident data is used to determine the Weighted Severity Index, which in turn is used to identify the blackspots. Thereafter, the Kernel Density tool is used in the ArcGIS software to locate blackspots on the map. The different characteristics of the blackspots are analysed such as time of occurrence of RTAs, type of collisions occurring in RTAs and the degree of involvement of the various categories of motor vehicles in RTAs along the stretch. The factors leading to RTAs along the blackspots are identified and suitable countermeasures are suggested.
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