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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| Format: | Article |
| Language: | English |
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University of Zagreb, Faculty of Transport and Traffic Sciences
2025-03-01
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| Series: | Promet (Zagreb) |
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| 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. |
| format | Article |
| id | doaj-art-4fb4ca76c24d434281e31ebf7bc23c9b |
| institution | OA Journals |
| issn | 0353-5320 1848-4069 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | University of Zagreb, Faculty of Transport and Traffic Sciences |
| record_format | Article |
| series | Promet (Zagreb) |
| 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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