Driver Inattention Detection in the Context of Next-Generation Autonomous Vehicles Design: A Survey

被引:0
|
作者
El Khatib, Alaa [1 ]
Ou, Chaojie [1 ]
Karray, Fakhri [1 ]
机构
[1] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2V 3G1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Autonomous vehicles; vehicle safety; DISTRACTION DETECTION; MENTAL WORKLOAD; BEHAVIOR; EYE; CLASSIFICATION; REAL; RECOGNITION; NONCONTACT; SLEEPINESS; INCIDENTS;
D O I
10.1109/TITS.2019.2940874
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Driver inattention is among major contributing factors to traffic accidents. There have been and continue to be efforts by governing bodies, car manufacturers, and researchers to prevent driver inattention or, failing that, to mitigate its effects. Many vehicles nowadays come equipped with driver monitoring systems that can alert the driver to, or compensate for, inattention. Moreover, the research community continues to explore and investigate more robust approaches to deal with inattention. Meanwhile, vehicle automation, to various degrees, is becoming more prevalent, with the human's role in the driving task changing depending on the level of autonomy. This necessitates that inattention detection, moving forward, be studied and designed in view of automation and in the context of a specific level of vehicle autonomy. Driver inattention and vehicle automation interact in a complex way, and that needs to be taken into account in the design of future vehicles. We explore this interaction in this paper in light of research findings, and survey inattention detection systems and attempt to contextualize them within popular frameworks for next-generation autonomous vehicles.
引用
收藏
页码:4483 / 4496
页数:14
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