An AI-driven support system for detecting distracted driving behaviour and improving safe driving

Accidents often result from diminishing driving skills and reduced attention, a problem that is becoming more prevalent with the aging population. Moreover, the rise in infotainment functions in vehicles poses another challenge, further distracting drivers from their primary task. Recognising the gravity of this situation, this paper presents an advanced intelligent driving support system to identify distracted driving behaviours. The core of our detection mechanism is based on YOLOv5m algorithm, which is fine-tuned with hyperparameter optimisation. The proposed system is able to recognise various distracted driving behaviours by analysing the driver's hand movements. By evaluating the proposed system, we observed that the use of a batch size of 8 and conducting 200 epochs produced the highest classification accuracy. The detecting hand manipulations of In-Vehicle Infotainment (IVI) system were identified with 100% accuracy. Also, cell phone use was detected with a probability exceeding 90%. Moreover, the system successfully can forecast the distracted driving behaviour when the vehicle is moving.

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Publication Details

Journal
International Journal of Grid and Utility Computing
Published
2025-01-01
DOI
https://doi.org/10.1504/ijguc.2025.145178
Citations
1
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.68
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article

An AI-driven support system for detecting distracted driving behaviour and improving safe driving

Naoki Tanaka, Leonard Barolli, Hibiki Tanaka, Makoto Ikeda
1 citations
International Journal of Grid and Utility Computing
Autonomous Vehicle Technology and Safety
0.68
article

An AI-driven support system for detecting distracted driving behaviour and improving safe driving

Naoki Tanaka, Leonard Barolli, Hibiki Tanaka, Makoto Ikeda
article en
1 citations

Abstract

Accidents often result from diminishing driving skills and reduced attention, a problem that is becoming more prevalent with the aging population. Moreover, the rise in infotainment functions in vehicles poses another challenge, further distracting drivers from their primary task. Recognising the gravity of this situation, this paper presents an advanced intelligent driving support system to identify distracted driving behaviours. The core of our detection mechanism is based on YOLOv5m algorithm, which is fine-tuned with hyperparameter optimisation. The proposed system is able to recognise various distracted driving behaviours by analysing the driver's hand movements. By evaluating the proposed system, we observed that the use of a batch size of 8 and conducting 200 epochs produced the highest classification accuracy. The detecting hand manipulations of In-Vehicle Infotainment (IVI) system were identified with 100% accuracy. Also, cell phone use was detected with a probability exceeding 90%. Moreover, the system successfully can forecast the distracted driving behaviour when the vehicle is moving.

International Journal of Grid and Utility ComputingVol. 16(2)
Fukuoka Institute of Technology (JP)
Openalex Percentile: Top 33%
Autonomous Vehicle Technology and Safety
0.68
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An AI-driven support system for detecting distracted driving behaviour and improving safe driving — Naoki Tanaka, Leonard Barolli, et al. · International Journal of Grid and Utility Computing (2025) | TGRS Research Map | TGRS