A systematic review on sensor-based driver behaviour studies: Coherent taxonomy, motivations, challenges, recommendations, substantial analysis and future directions

Al-Hussein, Ward Ahmed and Kiah, Miss Laiha Mat and Yee, Por Lip and Zaidan, B. B. (2021) A systematic review on sensor-based driver behaviour studies: Coherent taxonomy, motivations, challenges, recommendations, substantial analysis and future directions. PeerJ Computer Science, 7. ISSN 2376-5992, DOI https://doi.org/10.7717/peerj-cs.632.

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Abstract

In the plan and development of Intelligent Transportation Systems (ITS), understanding drivers behaviour is considered highly valuable. Reckless driving, incompetent preventive measures, and the reliance on slow and incompetent assistance systems are attributed to the increasing rates of traffic accidents. This survey aims to review and scrutinize the literature related to sensor-based driver behaviour domain and to answer questions that are not covered so far by existing reviews. It covers the factors that are required in improving the understanding of various appropriate characteristics of this domain and outlines the common incentives, open confrontations, and imminent commendations from former researchers. Systematic scanning of the literature, from January 2014 to December 2020, mainly from four main databases, namely, IEEEXplore, ScienceDirect, Scopus and Web of Science to locate highly credible peer-reviewed articles. Amongst the 5,962 articles found, a total of 83 articles are selected based on the author's predefined inclusion and exclusion criteria. Then, a taxonomy of existing literature is presented to recognize the various aspects of this relevant research area. Common issues, motivations, and recommendations of previous studies are identified and discussed. Moreover, substantial analysis is performed to identify gaps and weaknesses in current literature and guide future researchers into planning their experiments appropriately. Finally, future directions are provided for researchers interested in driver profiling and recognition. This survey is expected to aid in emphasizing existing research prospects and create further research directions in the near future.

Item Type: Article
Funders: Fundamental Research Grant Scheme (FRGS)[FP114-2018A], Ministry of Education, Malaysia
Uncontrolled Keywords: Driver behaviour; Sensors; ADAS; Intelligent transportation systems; Naturalistic driving; Traffic safety
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 18 Apr 2022 01:25
Last Modified: 18 Apr 2022 01:25
URI: http://eprints.um.edu.my/id/eprint/26755

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