Spatial Analysis of Urban Road Traffic Accidents Using GIS

Abstract

Road traffic accidents are on the rise in urban areas globally, including Sri Lanka, leading to significant human and property losses. The Colombo Municipal Council (CMC) area in Sri Lanka witnesses a particularly high number of these accidents. This study aimed to analyze urban traffic accidents using GIS within complex urban networks. It employed a two-step approach, starting with a hot spot analysis based on accident times and types (fatal, non-grievous, and damage-only), using Kernel Density Estimation (KDE) and Nearest Neighbor Hierarchy (NNH) methods. Additionally, it created separate severity maps and compares the results visually, with KDE offering a comprehensive overview and NNH pinpointing high-accident areas. The KDE method was expected to benefit long-term traffic congestion reduction and safety enhancement. NNH's severity map provides immediate insights for road safety specialists. A mathematical approach involved calculating the Prediction Accuracy Index (PAI) for each method, revealing a notably higher value for NNH, making it a more suitable choice. In conclusion, this study recommended the Nearest Neighbor Hierarchy (NNH) method as superior for road safety analysis, offering important guidance for urban planning and accident prevention efforts