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A Review on Existing Technologies for the Identification and Measurement of Abnormal Driving

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Abstract

Driving error is one of the crucial contributing factors to the increasing number of traffic deaths all over the world. Both external and internal stimuli significantly affect the driving performance of individuals, irrespective of their mild, moderate, or aggressive driving styles. Continued research is being performed to increase the efficiency of vehicle safety systems and improvise existing autonomous and semi-autonomous vehicles. This paper reviews the existing state-of-the-art technologies for different types of abnormal driving detection. The review is categorized into three sections i.e., abnormal driving detection using i) vehicular features, ii) physiological features, and iii) hybrid features. Various approaches have been compared for abnormal driving detection and areas for improvement are distilled. The research gaps identified lie in the lack of i) consideration of environmental data, ii) non-invasive physiological data, and iii) comparative studies among different types of driving abnormalities.

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  1. Indian Institute of Technology, Kharagpur, Kharagpur, India

    Ishita Sar, Aurobinda Routray & Biswajit Mahanty

  2. Department of Industrial and Systems Engineering, Indian Institute of Technology, Kharagpur, Kharagpur, India

    Ishita Sar & Biswajit Mahanty

  3. Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, Kharagpur, India

    Aurobinda Routray

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Sar, I., Routray, A. & Mahanty, B. A Review on Existing Technologies for the Identification and Measurement of Abnormal Driving. Int. J. ITS Res. 21, 159–177 (2023). https://doi.org/10.1007/s13177-023-00343-7

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