Iraqi Journal for Computer Science and Mathematics (Jul 2024)
Taxonomy, Open Challenges, Motivations, and Recommendations in Driver Behavior Recognition: A Systematic Review
Abstract
Driver behavior has a major role in many of the unpleasant things that happen when driving, such as crashes or accidents, heavy traffic, abrupt braking, and acceleration and deceleration. Numerous investigations have been carried out to look into the variables influencing driving behavior. To offer a thorough analysis and classify these findings according to a logical classification, further research is required. The goal of this systematic review is to enhance knowledge about the variables influencing driving behavior. A taxonomy on the subject of driver behavior in various ITS domains and their categories was also produced by this work. A systematic review of the literature was performed in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to gain insight into driver behaviour recognition. Specifically, IEEE Explore, ScienceDirect and Springer databases were searched to identify any relevant articles with a focus on "driver behavior," "driver style," "driver pattern," "driver simulator," and "visual attention,” from 2008 to 2021 (15 April). Several filtering and scanning procedures were performed on all 606 retrieved articles in compliance with the exclusion/inclusion criteria; nonetheless, only 50 articles met the requirements. The criteria-compliant references were examined and evaluated. Furthermore, every piece that was included was classified using a taxonomy. The four categories created by the taxonomy are review, experiment, framework, and other study types. To illustrate the main gaps in the literature regarding the identification of driving behavior, a discussion and analysis were presented. This thorough analysis has highlighted the issues and reasons while also pointing forth fresh research directions.
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