ArticleSensors (Basel, Switzerland)2017
Automatic Detection of Driver Fatigue Using Driving Operation Information for Transportation Safety.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- A fatigue driving detection method based on driver posture and facial state analysis.Scientific reports · 2026Article
- Vibration analysis and optimal design of tracked vehicle's seat suspension for improving combat efficiency.Scientific reports · 2025Article
- Real-Time Driver Attention Detection in Complex Driving Environments via Binocular Depth Compensation and Multi-Source Temporal Bidirectional Long Short-Term Memory Network.Sensors (Basel, Switzerland) · 2025Article
- A Novel Neural Network Model Based on Real Mountain Road Data for Driver Fatigue Detection.Biomimetics (Basel, Switzerland) · 2025Article
- Review
- Real-Time Deep Learning-Based Drowsiness Detection: Leveraging Computer-Vision and Eye-Blink Analyses for Enhanced Road Safety.Sensors (Basel, Switzerland) · 2023Article
- NON-INTRUSIVE DROWSINESS DETECTION TECHNIQUES AND THEIR APPLICATION IN DETECTING EARLY DEMENTIA IN OLDER DRIVERS.Proceedings of the Future Technologies Conference (FTC) 2022. Volume 2. Future Technologies Conference (7th : 2022 : Vancouver, B.C.; Online) · 2023Article
- Speed Management Strategy: Designing an IoT-Based Electric Vehicle Speed Control Monitoring System.Sensors (Basel, Switzerland) · 2021Article
- Evaluation of a Fatigue Detector Using Eye Closure-Associated Indicators Acquired from Truck Drivers in a Simulator Study.Sensors (Basel, Switzerland) · 2021Article
- Design of Smart Steering Wheel for Unobtrusive Health and Drowsiness Monitoring.Sensors (Basel, Switzerland) · 2021Article
- EEG-Based Driving Fatigue Detection Using a Two-Level Learning Hierarchy Radial Basis Function.Frontiers in neurorobotics · 2021Article
- Effects of a Motion Seat System on Driver's Passive Task-Related Fatigue: An On-Road Driving Study.Sensors (Basel, Switzerland) · 2020Article
- A Comprehensive Survey of Driving Monitoring and Assistance Systems.Sensors (Basel, Switzerland) · 2019Review
- A Review of Psychophysiological Measures to Assess Cognitive States in Real-World Driving.Frontiers in human neuroscience · 2019Review
Corrections and comments
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Fatigued driving is a major cause of road accidents. For this reason, the method in this paper is based on the steering wheel angles (SWA) and yaw angles (YA) information under real driving conditions to detect drivers' fatigue levels. It analyzes the operation features of SWA and YA under different fatigue statuses, then calculates the approximate entropy (ApEn) features of a short sliding window on time series. Using the nonlinear feature construction theory of dynamic time series, with the fatigue features as input, designs a "2-6-6-3" multi-level back propagation (BP) Neural Networks classifier to realize the fatigue detection. An approximately 15-h experiment is carried out on a real road, and the data retrieved are segmented and labeled with three fatigue levels after expert evaluation, namely "awake", "drowsy" and "very drowsy". The average accuracy of 88.02% in fatigue identification was achieved in the experiment, endorsing the value of the proposed method for engineering applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.