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Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review

Current road accident research focuses mainly on the key role and importance of Artificial Intelligence (AI) in road accident analysis and prevention. After reviewing the literature, this study found that AI had a wide range of potential applications. It can analyse traffic data more accurately and...

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Main Authors: Sun, Wei, Abdullah, Lili Nurliyana, Khalid, Fatimah, Sulaiman, Puteri Suhaiza
Format: Article
Published: Human Resource Management Academic Research Society 2023
Online Access:http://psasir.upm.edu.my/id/eprint/108958/
https://hrmars.com/index.php/IJARBSS/article/view/19260/Intelligent-Analysis-of-Vehicle-Accidents-to-Detect-Road-Safety-A-Systematic-Literature-Review
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spelling my.upm.eprints.1089582024-05-17T02:35:02Z http://psasir.upm.edu.my/id/eprint/108958/ Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review Sun, Wei Abdullah, Lili Nurliyana Khalid, Fatimah Sulaiman, Puteri Suhaiza Current road accident research focuses mainly on the key role and importance of Artificial Intelligence (AI) in road accident analysis and prevention. After reviewing the literature, this study found that AI had a wide range of potential applications. It can analyse traffic data more accurately and quickly through advanced machine learning and deep learning technologies, and identify accident risks and dangerous driving behaviours, thereby helping to predict and avoid accidents. Furthermore, the research provides insight into the different types of traffic accidents and the severity of injuries they cause, highlighting the importance of understanding these differences to improve road safety and help inform decision-making. The paper has attempted to develop a comprehensive and diverse road crash impact model by exploring some of the elements that influence road crashes, including human factors, vehicle factors and road environment factors. Finally, this paper identifies some innovations and future research directions for this study, including addressing imbalances and quality issues in collecting and processing data, improving the interpretability and transparency of injury severity expressions, and adopting a more comprehensive approach to analysing road crashes. These innovations will promote greater theoretical and practical progress in road crash research to improve road safety and reduce the damage caused by accidents. Human Resource Management Academic Research Society 2023 Article PeerReviewed Sun, Wei and Abdullah, Lili Nurliyana and Khalid, Fatimah and Sulaiman, Puteri Suhaiza (2023) Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review. International Journal of Academic Research in Business and Social Sciences, 13 (11). pp. 306-321. ISSN 2222-6990 https://hrmars.com/index.php/IJARBSS/article/view/19260/Intelligent-Analysis-of-Vehicle-Accidents-to-Detect-Road-Safety-A-Systematic-Literature-Review 10.6007/IJARBSS/v13-i11/19260
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Current road accident research focuses mainly on the key role and importance of Artificial Intelligence (AI) in road accident analysis and prevention. After reviewing the literature, this study found that AI had a wide range of potential applications. It can analyse traffic data more accurately and quickly through advanced machine learning and deep learning technologies, and identify accident risks and dangerous driving behaviours, thereby helping to predict and avoid accidents. Furthermore, the research provides insight into the different types of traffic accidents and the severity of injuries they cause, highlighting the importance of understanding these differences to improve road safety and help inform decision-making. The paper has attempted to develop a comprehensive and diverse road crash impact model by exploring some of the elements that influence road crashes, including human factors, vehicle factors and road environment factors. Finally, this paper identifies some innovations and future research directions for this study, including addressing imbalances and quality issues in collecting and processing data, improving the interpretability and transparency of injury severity expressions, and adopting a more comprehensive approach to analysing road crashes. These innovations will promote greater theoretical and practical progress in road crash research to improve road safety and reduce the damage caused by accidents.
format Article
author Sun, Wei
Abdullah, Lili Nurliyana
Khalid, Fatimah
Sulaiman, Puteri Suhaiza
spellingShingle Sun, Wei
Abdullah, Lili Nurliyana
Khalid, Fatimah
Sulaiman, Puteri Suhaiza
Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
author_facet Sun, Wei
Abdullah, Lili Nurliyana
Khalid, Fatimah
Sulaiman, Puteri Suhaiza
author_sort Sun, Wei
title Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
title_short Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
title_full Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
title_fullStr Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
title_full_unstemmed Intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
title_sort intelligent analysis of vehicle accidents to detect road safety: a systematic literature review
publisher Human Resource Management Academic Research Society
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/108958/
https://hrmars.com/index.php/IJARBSS/article/view/19260/Intelligent-Analysis-of-Vehicle-Accidents-to-Detect-Road-Safety-A-Systematic-Literature-Review
_version_ 1800093823363186688
score 13.211869

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