Innovative Framework for Distracted-Driving Alert System Based on Deep Learning

• Published in: IEEE access Vol. 10; pp. 77523 - 77536
• Main Authors: Lin, Peng-Wei, Hsu, Chih-Ming
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accidents; Artificial neural networks; Behavioral sciences; Cargo ships; Convolutional neural network; Deep learning; distracted-driving recognition; Drinking water; Driver behavior; Driving; driving-safety alert system; Electroencephalography; Feature extraction; LiDAR-based 3D-object detection; Perception; Recognition; Road conditions; Safety; Sensors; time-to-collision; Traffic accidents; Traffic accidents & safety; Traffic safety; Traffic signals; Vehicles

Distracted driving is the most common cause of traffic accidents. According to a World Health Organization report, the number of traffic accidents has been increasing in recent years. To address this issue, distracted-driving recognition is an important area of traffic safety research. However, dist...