Work

Fatigue Driving Detection Based on Convolutional Neural Network Model Connected to New Energy Vehicles

Year: 2025

Type: article

Abstract: Fatigue driving detection based on Convolutional Neural Network (CNN) is a method that utilizes deep learning technology to monitor and identify whether a driver is in a fatigued state in real-time. This method analyzes the driver's facial features, eye status, and other information, combining multiple algorithms and techniques to achieve accurate detection and early warning of fatigue driving. This paper takes the application comparison of Yolov8 model as an example to conduct research on the idea of integrating fatigue detection systems with the Internet of Vehicles. During driving, if fatigue driving occurs, the system will make a judgment. Then, the autonomous driving system will take over the driving of the car and remind the driver to enter a rest area or stop to rest.

Source: Theory and Practice of Science and Technology

DOI: 10.47297/taposatwsp2633-456927.20250602

Author: Xiang Li

Institutions: Kunming University of Science and Technology, Oxbridge College

Language: English

Topic: Sleep and Work-Related Fatigue

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: bronze

OpenAlex ID: W4408870119