驾驶员疲劳预测:方法和公开挑战

Hilal Abbood, W. Al-Nuaimy, Ali Al-Ataby, Sameh A. Salem, Hamzah S. AlZu'bi
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引用次数: 23

摘要

疲劳是一种逐渐增长的心理过程,影响人的反应时间和意识。它是全球道路致命事故的原因之一。尽管现在人们普遍认为疲劳在道路安全中起着重要作用,但这在很大程度上仍然是由司机个人来管理的。目前该领域的研究主要集中在疲劳检测上,现有的系统主要是对处于严重疲劳阶段的驾驶员进行预警。这些系统利用疲劳的生理信号或行为反应来发出警报。本研究探讨了使用一组疲劳症状(如瞳孔反应、凝视模式、转向反应和脑电图)来构建一个鲁棒的疲劳检测算法的可行性,该算法可用于现实生活系统,用于早期预测和避免疲劳发展。需要密集的测试和验证阶段,以确保系统的可靠性和适用性,应该能够在不同程度的疲劳下检测疲劳水平。此外,提出的系统预测疲劳的后续阶段,并为每个驾驶员生成近似的行为模型,以实现更个性化和有效的干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of driver fatigue: Approaches and open challenges
Fatigue is a mental process that grows gradually and affects human reaction time and the consciousness. It is one of the causes of road fatal accidents around the globe. Although it is now generally accepted that fatigue plays an important role in road safety, it is still largely left to individual drivers to manage. The recent research in this area focuses on fatigue detection and the existing systems alert the drivers in severe fatigued stage. These systems use either physiological signs of the fatigue or the behavioural reaction to generate alerts. This research investigates the feasibility of using a group of fatigue symptoms (such as pupil response, gaze patterns, steering reaction and EEG) to build a robust fatigue detection algorithm that can be used in a real-life system for the early prediction and avoidance of fatigue development. Intensive testing and validation stages are required to ensure the reliability and the suitability of the system that should be able to detect fatigue levels at different degrees of tiredness. Moreover, the proposed system predicts subsequent stages of fatigue and generates an approximate behavioural model for each individual driver to enable more personalised and effective intervention.
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