Review of driving-behaviour simulation: VISSIM and artificial intelligence approach
Examining driving behaviour is crucial for traffic operations because of its influence on driver safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately 95% of severe traffic collisions can be attributed to human error. With the progress in artificial intell...
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Elsevier Ltd
2025
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| author | Al-Msari H. Koting S. Ahmed A.N. El-shafie A. |
| author2 | 57223256689 |
| author_facet | 57223256689 Al-Msari H. Koting S. Ahmed A.N. El-shafie A. |
| author_sort | Al-Msari H. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Examining driving behaviour is crucial for traffic operations because of its influence on driver safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately 95% of severe traffic collisions can be attributed to human error. With the progress in artificial intelligence in recent decades, notable advancements have been achieved in computer capabilities, communication systems and data collection technology. This increase has significantly influenced our capacity to replicate driver behaviour and comprehend underlying driving mechanisms in diverse situations. Traffic microsimulation facilitates an understanding of traffic performance inside a given road network. Among the microsimulation software packages, Verkehr In St�dten ? SIMulationsmodell (VISSIM) has garnered significant attention owing to its notable ability to accurately replicate traffic circumstances with high dependability in real-world scenarios. Given the diverse applicability of VISSIM-based schemes, this review systematically examines the applications of the VISSIM-based driving-behaviour models within different research contexts, revealing their utility. This review is designed to provide guidance for researchers in selecting the most suitable methodological approach tailored to their specific research objectives and constraints when utilising VISSIM. Five important aspects, including calibration, driving behaviour, incident, and heterogeneous traffic simulation, as well as utilisation of artificial intelligence with VISSIM, are assessed, which could yield substantial advantages in advancing more precise and authentic driving-behaviour modelling in VISSIM. ? 2024 The Authors |
| format | Article |
| id | my.uniten.dspace-36707 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Elsevier Ltd |
| record_format | dspace |
| spelling | my.uniten.dspace-367072025-03-03T15:44:04Z Review of driving-behaviour simulation: VISSIM and artificial intelligence approach Al-Msari H. Koting S. Ahmed A.N. El-shafie A. 57223256689 55839645200 57214837520 16068189400 Examining driving behaviour is crucial for traffic operations because of its influence on driver safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately 95% of severe traffic collisions can be attributed to human error. With the progress in artificial intelligence in recent decades, notable advancements have been achieved in computer capabilities, communication systems and data collection technology. This increase has significantly influenced our capacity to replicate driver behaviour and comprehend underlying driving mechanisms in diverse situations. Traffic microsimulation facilitates an understanding of traffic performance inside a given road network. Among the microsimulation software packages, Verkehr In St�dten ? SIMulationsmodell (VISSIM) has garnered significant attention owing to its notable ability to accurately replicate traffic circumstances with high dependability in real-world scenarios. Given the diverse applicability of VISSIM-based schemes, this review systematically examines the applications of the VISSIM-based driving-behaviour models within different research contexts, revealing their utility. This review is designed to provide guidance for researchers in selecting the most suitable methodological approach tailored to their specific research objectives and constraints when utilising VISSIM. Five important aspects, including calibration, driving behaviour, incident, and heterogeneous traffic simulation, as well as utilisation of artificial intelligence with VISSIM, are assessed, which could yield substantial advantages in advancing more precise and authentic driving-behaviour modelling in VISSIM. ? 2024 The Authors Final 2025-03-03T07:44:04Z 2025-03-03T07:44:04Z 2024 Article 10.1016/j.heliyon.2024.e25936 2-s2.0-85185266378 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185266378&doi=10.1016%2fj.heliyon.2024.e25936&partnerID=40&md5=4f791a5facde9eda370bfc74ce654cb7 https://irepository.uniten.edu.my/handle/123456789/36707 10 4 e25936 All Open Access; Gold Open Access; Green Open Access Elsevier Ltd Scopus |
| spellingShingle | Al-Msari H. Koting S. Ahmed A.N. El-shafie A. Review of driving-behaviour simulation: VISSIM and artificial intelligence approach |
| title | Review of driving-behaviour simulation: VISSIM and artificial intelligence approach |
| title_full | Review of driving-behaviour simulation: VISSIM and artificial intelligence approach |
| title_fullStr | Review of driving-behaviour simulation: VISSIM and artificial intelligence approach |
| title_full_unstemmed | Review of driving-behaviour simulation: VISSIM and artificial intelligence approach |
| title_short | Review of driving-behaviour simulation: VISSIM and artificial intelligence approach |
| title_sort | review of driving-behaviour simulation: vissim and artificial intelligence approach |
| url_provider | http://dspace.uniten.edu.my/ |