A literature review: AI models for road safety for prediction of crash frequency and severity
Abstract Artificial intelligence and machine learning have brought a new paradigm in road safety, moving from the traditional approach to adopting data-driven techniques for predicting the frequency and severity of crashes. This review gives the main research contributions and highlights works towar...
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| Format: | Article |
| Language: | English |
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Springer
2025-05-01
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| Series: | Discover Civil Engineering |
| Online Access: | https://doi.org/10.1007/s44290-025-00255-3 |
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| _version_ | 1850231078724304896 |
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| author | Muneeb Shehzad Butt Muhammad Awais Shafique |
| author_facet | Muneeb Shehzad Butt Muhammad Awais Shafique |
| author_sort | Muneeb Shehzad Butt |
| collection | DOAJ |
| description | Abstract Artificial intelligence and machine learning have brought a new paradigm in road safety, moving from the traditional approach to adopting data-driven techniques for predicting the frequency and severity of crashes. This review gives the main research contributions and highlights works toward integrating different data sets into one comprehensive safety assessment, starting from traffic patterns, environmental conditions, and driver behavior analytics. This research paper reviews how AI and ML are revolutionizing road safety: from basic statistical methods, such as Ordered Probit, to advanced Neural Networks and Deep Learning techniques. It provides rich detail on the dynamics of crashes to serve as a basis for intelligent traffic management and policy decisions. That's because what has transpired with the confluence of AI, ML, and road safety initiatives is a major step forward to reduce traffic incidents and improve roadway safety, from early statistical models to sophisticated systems capable of predicting crashes and identifying opportunities for intervention Fig. 2. |
| format | Article |
| id | doaj-art-5ea76dffd1a346f88b20f3a8f40dd58a |
| institution | OA Journals |
| issn | 2948-1546 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Civil Engineering |
| spelling | doaj-art-5ea76dffd1a346f88b20f3a8f40dd58a2025-08-20T02:03:39ZengSpringerDiscover Civil Engineering2948-15462025-05-012111410.1007/s44290-025-00255-3A literature review: AI models for road safety for prediction of crash frequency and severityMuneeb Shehzad Butt0Muhammad Awais Shafique1University of Central PunjabUniversity of Central PunjabAbstract Artificial intelligence and machine learning have brought a new paradigm in road safety, moving from the traditional approach to adopting data-driven techniques for predicting the frequency and severity of crashes. This review gives the main research contributions and highlights works toward integrating different data sets into one comprehensive safety assessment, starting from traffic patterns, environmental conditions, and driver behavior analytics. This research paper reviews how AI and ML are revolutionizing road safety: from basic statistical methods, such as Ordered Probit, to advanced Neural Networks and Deep Learning techniques. It provides rich detail on the dynamics of crashes to serve as a basis for intelligent traffic management and policy decisions. That's because what has transpired with the confluence of AI, ML, and road safety initiatives is a major step forward to reduce traffic incidents and improve roadway safety, from early statistical models to sophisticated systems capable of predicting crashes and identifying opportunities for intervention Fig. 2.https://doi.org/10.1007/s44290-025-00255-3 |
| spellingShingle | Muneeb Shehzad Butt Muhammad Awais Shafique A literature review: AI models for road safety for prediction of crash frequency and severity Discover Civil Engineering |
| title | A literature review: AI models for road safety for prediction of crash frequency and severity |
| title_full | A literature review: AI models for road safety for prediction of crash frequency and severity |
| title_fullStr | A literature review: AI models for road safety for prediction of crash frequency and severity |
| title_full_unstemmed | A literature review: AI models for road safety for prediction of crash frequency and severity |
| title_short | A literature review: AI models for road safety for prediction of crash frequency and severity |
| title_sort | literature review ai models for road safety for prediction of crash frequency and severity |
| url | https://doi.org/10.1007/s44290-025-00255-3 |
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