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A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations

Author

Listed:
  • Sarah Najm Abdulwahid

    (College of Graduate Studies, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • Moamin A. Mahmoud

    (Institute of Informatics and Computing in Energy, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

  • Bilal Bahaa Zaidan

    (Future Technology Research Center, National Yunlin University of Science and Technology, Douliu 64002, Taiwan)

  • Abdullah Hussein Alamoodi

    (Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia)

  • Salem Garfan

    (Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia)

  • Mohammed Talal

    (Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Batu Pahat 86400, Malaysia)

  • Aws Alaa Zaidan

    (Department of Computing, Universiti Pendidikan Sultan Idris, Tanjong Malim 35900, Malaysia)

Abstract

With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011–2021). A number of digital databases (i.e., IEEE Xplore ® , ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.

Suggested Citation

  • Sarah Najm Abdulwahid & Moamin A. Mahmoud & Bilal Bahaa Zaidan & Abdullah Hussein Alamoodi & Salem Garfan & Mohammed Talal & Aws Alaa Zaidan, 2022. "A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations," IJERPH, MDPI, vol. 19(6), pages 1-38, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3552-:d:772955
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    References listed on IDEAS

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    1. Sarah Najm Abdulwahid & Moamin A. Mahmoud & Nazrita Ibrahim & Bilal Bahaa Zaidan & Hussein Ali Ameen, 2022. "Modeling Motorcyclists’ Aggressive Driving Behavior Using Computational and Statistical Analysis of Real-Time Driving Data to Improve Road Safety and Reduce Accidents," IJERPH, MDPI, vol. 19(13), pages 1-20, June.
    2. Marija Ferko & Dario Babić & Darko Babić & Ali Pirdavani & Marko Ševrović & Marijan Jakovljević & Grgo Luburić, 2022. "Influence of Road Safety Barriers on the Severity of Motorcyclist Injuries in Horizontal Curves," Sustainability, MDPI, vol. 14(22), pages 1-15, November.

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