Identification of Road Traffic Crash Blackspots on National and State Highways in Trivandrum, India Using Kernel Density Estimation

Abstract

The paper presents a comprehensive study on road traffic accidents (RTAs) in the Trivandrum district of Kerala, India, emphasizing the high incidence of fatalities and injuries, particularly on National and State Highways. The study utilizes Geographic Information System (GIS) technology to analyze spatial and temporal patterns of RTAs, employing Kernel Density Estimation (KDE) to identify accident as Blackspots, in the Thiruvananthapuram district. The study spans three years, from 2020 to 2022. It includes detailed crash data, including collision types, accident severity, weather conditions, road types, and junctions, revealing insights such as the prevalence of head-to-head collisions and the influence on accident rates. The Severity Index (SI) is introduced as a metric to quantify accident gravity. The research aims to identify blackspots for improving safety measures, ultimately contributing to the well-being of road users in Kerala. The findings underscore the urgent need for targeted road safety measures and infrastructure improvements to mitigate the risk of RTAs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.