A Novel Approach to Detect Drowsy Driving Resulting From Sleep Loss and Sleep Pressure

检测因睡眠不足和睡眠压力而导致的疲劳驾驶的新方法

• 批准号: 532224-2018
• 负责人: Fogel, Stuart
• 金额: $ 4.55万
• 依托单位: University of Ottawa
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=719074
• 关键词: Novel; Approach; Detect; Drowsy; Driving

Sleep loss has become a modern-day epidemic, with a significant impact on daytime functioning, resulting in about 6000 fatal car crashes/year due to drowsy driving in the US and about 100/year in Canada. One potentially life-threatening outcome is increased driver fatigue, often resulting in serious motor vehicle accidents. The main objective of the proposed research is the development of a non-invasive, real-time and unobtrusive in-vehicle system to detect driver fatigue before a motor vehicle accident occurs. Our proposed system measures eye movements that precede drowsiness using infra-red (IR) eye tracking camera technology. These eye movements are classified online by our novel artificial intelligence algorithms to detect the antecedents of somnolence, to be used to alert the driver while driving. Here, using driving simulation technology, we aim to study the relationship between eye movement characteristics and the behavioural and electrophysiological warning signs of impending driver sleepiness. This will allow us to develop a method to detect sleepiness and alert drivers before impairment and lapses in judgement occur. We plan to develop a novel method to effectively detect drowsiness using only eye tracking data in: 1) varying sleep-pressure, and, 2) natural variations in drowsiness at different times of day or night. Ultimately, this will result in the commercialization of an "early warning system", as a countermeasure to drowsiness impairment in the transport-trucking industry, public transit and in individual passenger vehicles. We expect that this work will open up further avenues for research and applications about the fitness to drive due to various other causes, such as alcohol, drug use and distracted driving.

睡眠不足已经成为一种现代流行病，对白天的功能有重大影响，导致美国每年约有6000起致命的车祸，加拿大每年约有100起。一个潜在的危及生命的后果是驾驶员疲劳增加，经常导致严重的机动车事故。该研究的主要目标是开发一种非侵入性、实时和不显眼的车载系统，以在机动车事故发生前检测驾驶员疲劳。我们提出的系统使用红外眼动追踪相机技术来测量睡意之前的眼球运动。这些眼球运动通过我们新颖的人工智能算法在线分类，以检测嗜睡的前兆，并在驾驶时用于提醒驾驶员。在这里，我们利用驾驶模拟技术，旨在研究眼动特征与驾驶员即将嗜睡的行为和电生理警告信号之间的关系。这将使我们能够开发出一种方法来检测困倦，并在驾驶员出现损伤和判断失误之前提醒驾驶员。我们计划开发一种新颖的方法，仅使用眼动追踪数据就能有效地检测睡意：1)不同的睡眠压力；2)白天或晚上不同时间睡意的自然变化。最终，这将导致“早期预警系统”的商业化，作为运输卡车运输业、公共交通和个别客运车辆的困倦障碍的对策。我们期望这项工作将为研究和应用由于各种其他原因（如酒精、药物使用和分心驾驶）导致的驾驶适应性开辟进一步的途径。