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Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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PUBLISHED
13.03.2025
DOI
https://doi.org/10.7307/ptt.v37i2.751
ISSUE
2025 (Vol 37), Issue 2
LICENSE
Copyright (c) 2025 Kaliprasana MUDULI, Deorishabh SAHU, Indrajit GHOSH
Creative Commons 4.0 logo
This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots

Authors:Kaliprasana MUDULI, Deorishabh SAHU, Indrajit GHOSH

Abstract

This study introduces a novel, adaptable framework for identifying and prioritising road traffic accident hotspots using the Getis Ord Gi* spatial autocorrelation tool. The framework classifies regions as hotspots or coldspots based on accident severity and frequency. A unique weighting system is developed to compute the Crash Severity Index (CSI), considering the severity of crashes in terms of fatalities and injuries. The identified hotspots are prioritised using the CSI, providing policymakers with a structured approach to allocate resources for crash remedial measures. The main contribution of this work is the development of a flexible framework applicable to various cities, states or countries to improve road safety. The framework’s effectiveness is demonstrated through a case study in Punjab, India, revealing that Sangrur, Hoshiarpur and Police Commissionerate Ludhiana are the top three hotspots. The study also offers a detailed analysis of crash statistics in Punjab, emphasising the severity of pedestrian crashes. This approach addresses the current lack of structured hotspot identification and prioritization strategies, marking a significant advancement in road safety management.

Keywords:road traffic accidents, hotspot identification, crash severity, spatial analysis, road safety management, resource allocation

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