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

Ward Ahmed Al-Hussein; Miss Laiha Mat Kiah; Por Lip Yee; B B Zaidan

doi:10.7717/peerj-cs.632

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

PeerJ Comput Sci. 2021 Aug 25:7:e632. doi: 10.7717/peerj-cs.632. eCollection 2021.

Authors

Ward Ahmed Al-Hussein¹, Miss Laiha Mat Kiah¹, Por Lip Yee¹, B B Zaidan²

Affiliations

¹ Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia.
² Department of Computing, Faculty of Arts, Universiti Pendidikan Sultan Idris, Perak, Malaysia.

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.

Keywords: ADAS; Driver behaviour; Intelligent transportation systems; Naturalistic driving; Sensors; Traffic safety.

Grants and funding

This work was supported by Fundamental Research Grant Scheme (FRGS) grant number FP114-2018A from the Ministry of Higher Education, Malaysia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.