Detection of the gaze direction of a driver using the time-varying image processing

Mita, S.; Norimatsu, Yuu; Itou, Souichi; Kozuka, Kazuhiro; Nakano, Tomoaki; Yamamoto, Shin

doi:10.1016/s0389-4304(03)00042-0

JSAE Review

2003

DOI: 10.1016/s0389-4304(03)00042-0

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Detection of the gaze direction of a driver using the time-varying image processing

S. Mita

Yuu Norimatsu

Souichi Itou

et al.

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“…Currently, studies focus on driving fatigue theories ( 23 – 25 ), driving fatigue measurement methods, and ways of reducing these ( 26 , 27 ). The study on technology for monitoring driver fatigue mainly refers to the behavioral changes of drivers and fluctuations in physiological symptoms related to fatigue in driving situations, involving electroencephalogram (EEG) ( 28 ), electrocardiogram (ECG) ( 29 , 30 ), eye-movement activity ( 31 – 33 ), body posture (e.g., head motion track) ( 34 ), facial thermography ( 15 , 35 , 36 ), and steering wheel parameter ( 37 – 39 ). Hess also found that a driver experiences a significant drop in critical flicker-fusion (CFF) after a long time driving ( 40 ), so that analyzing a driver’s objective response performance, such as memory and reaction time, is also an effective approach for research.…”

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confidence: 99%

Assessment of Urban Railway Transit Driver Workload and Fatigue under Real Working Conditions

Huang

Liu

et al. 2019

Transportation Research Record

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This paper describes an experiment conducted to establish a workload model by employing physiological methods to measure driver workload and fatigue under real working conditions. Experienced healthy metro drivers were selected as subjects; they performed normal schedules during which simultaneous electrocardiogram (ECG) recording was used to assess their levels of fatigue. Then, subjective workload assessment and reaction time tests were conducted during each break interval to monitor the drivers’ physiological and psychological performance. Based on task analysis, driving workload models with time weight parameters of four types of tasks were established and the workload real-time changes during different shifts were evaluated. The results demonstrate that workload tends to increase over time and it is significantly higher during manual driving mode than autonomous mode ( p = 0.015 < 0.05). Driving fatigue occurs earlier in the night shift than in the day shift according to ECG spectrum analysis results. Although the results of reaction time tests show no significance ( p = 0.917 > 0.05), the increase in the number of reaction errors after fatigue driving indicates a reduction in drivers’ cognitive ability. Regression analysis shows a significant regression relationship with a mutual incentive effect between workload and fatigue in three shifts ( R2 > 0.4). These will be used as a future reference for fatigue research and to help develop reasonable schedules to ensure operational safety.

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Assessment of Urban Railway Transit Driver Workload and Fatigue under Real Working Conditions

Huang

Liu

et al. 2019

Transportation Research Record

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A driver-distraction-based lane-keeping assistance system

Pohl

Birk

Westervall

2007

Proceedings of the Institution of Mechanical Engineers, Part I:

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Single-vehicle roadway departure (SVRD) accidents occur in many cases owing to driver distraction or drowsiness constituting a substantial share of today's road vehicle accidents and casualties. This paper describes a distraction-based lane-keeping support system, which intervenes only when the driver is positively detected as being distracted. Distraction here is understood as cognitive and visual distraction, and the focus of this system is on the latter one. In order to estimate the driver's visual distraction level, a video-based driver monitoring system is used. Lane-keeping support is provided by an additional torque applied on the steering shaft in order to regain an appropriate lane position. In this manner the system only intervenes when the vehicle has drifted out of its lane and while the driver is distracted. Test track investigations indicate large opportunities for such a system from a driver perspective, provided that sufficient reliability of the employed vision sensor for lane and face tracking can be obtained.

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Detection of the gaze direction of a driver using the time-varying image processing

Cited by 2 publications

References 1 publication

Assessment of Urban Railway Transit Driver Workload and Fatigue under Real Working Conditions

Assessment of Urban Railway Transit Driver Workload and Fatigue under Real Working Conditions

A driver-distraction-based lane-keeping assistance system

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