An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots

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 de...

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Main Authors: Kaliprasana MUDULI, Deorishabh SAHU, Indrajit GHOSH
Format: Article
Language:English
Published: University of Zagreb, Faculty of Transport and Traffic Sciences 2025-03-01
Series:Promet (Zagreb)
Subjects:
Online Access:https://traffic2.fpz.hr/index.php/PROMTT/article/view/751
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author Kaliprasana MUDULI
Deorishabh SAHU
Indrajit GHOSH
author_facet Kaliprasana MUDULI
Deorishabh SAHU
Indrajit GHOSH
author_sort Kaliprasana MUDULI
collection DOAJ
description 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.
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language English
publishDate 2025-03-01
publisher University of Zagreb, Faculty of Transport and Traffic Sciences
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spelling doaj-art-4fb4ca76c24d434281e31ebf7bc23c9b2025-08-20T02:04:59ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692025-03-0137232133710.7307/ptt.v37i2.751751An Adaptable Framework for Identifying and Prioritising Road Traffic Accident HotspotsKaliprasana MUDULI0Deorishabh SAHU1Indrajit GHOSH2Indian Institute of Technology Roorkee, Department of Civil Engineering, Transportation Engineering GroupIndian Institute of Technology Roorkee, Department of Civil Engineering, Transportation Engineering GroupIndian Institute of Technology Roorkee, Department of Civil Engineering, Transportation Engineering GroupThis 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.https://traffic2.fpz.hr/index.php/PROMTT/article/view/751road traffic accidentshotspot identificationcrash severityspatial analysisroad safety managementresource allocation
spellingShingle Kaliprasana MUDULI
Deorishabh SAHU
Indrajit GHOSH
An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots
Promet (Zagreb)
road traffic accidents
hotspot identification
crash severity
spatial analysis
road safety management
resource allocation
title An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots
title_full An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots
title_fullStr An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots
title_full_unstemmed An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots
title_short An Adaptable Framework for Identifying and Prioritising Road Traffic Accident Hotspots
title_sort adaptable framework for identifying and prioritising road traffic accident hotspots
topic road traffic accidents
hotspot identification
crash severity
spatial analysis
road safety management
resource allocation
url https://traffic2.fpz.hr/index.php/PROMTT/article/view/751
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AT kaliprasanamuduli adaptableframeworkforidentifyingandprioritisingroadtrafficaccidenthotspots
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