Detrimental effects of carryover of eye movement behaviour on hazard perception accuracy: Effects of driver experience, difficulty of task, and hazardousness of road

Hills, PH; Thompson, Catherine; Pake, J. Michael

doi:10.1016/j.trf.2018.07.014

Cited by 25 publications

(35 citation statements)

References 51 publications

(67 reference statements)

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“…However, a driver's cognitive method also affects the fixation duration, which was found in previous studies. Novice drivers are more likely to be involved in road accidents than experienced drivers and this relates to their lower performance in hazard perception tasks (Hills, Thompson, & Pake, 2018). Fixation duration is related to the driver's cognitive method (Levy, Golkin, Borowsky, & Vakil, 2019), which is a limitation of this study.…”

Section: Discussionmentioning

confidence: 99%

Study on drivers' visual perception characteristics during the take‐over of vehicle control in automated driving

Niu

Sun

et al. 2020

Hum Ftrs & Erg Mfg Svc

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A high degree of automated driving distracts drivers more easily, resulting in slow recognition of critical events during driving and slow responses to emergencies. Automated driving and manual switching processes are also prone to erroneous decisions. We conducted a simulated automated driving experiment to study participants' visual perception characteristics during the takeover of vehicle control. The present study used dynamic videos to imitate the driving situations when drivers returned their gaze from the distractive source to the road. We collected the drivers' eye movement data to analyze the search strategy and physiological characteristics of the drivers after the takeover reminder. The results showed that the instant information search method of the drivers was scanning of the driving scene. When the degree of distraction deepened and the hazard level of scenes increased, the pupil diameter of the drivers increased and the fixation duration became longer. These findings can help to design takeover warnings and support more intelligent automated driving systems to judge whether measures should be taken to interfere with the driver's operation to avoid collisions. Furthermore, the drivers' fixation point distribution focused on the left side and the lower side of the scene. We suggest that the takeover warning is displayed in the head-up display. This study provides a better understanding of drivers' visual perception characteristics when drivers' eyesight returns from other distractors to the driving scene and a good theoretical basis for the design of hazard warning information for automated driving.

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Section: Discussionmentioning

confidence: 99%

Study on drivers' visual perception characteristics during the take‐over of vehicle control in automated driving

Niu

Sun

et al. 2020

Hum Ftrs & Erg Mfg Svc

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“…32,33 Novice drivers had lower performance in riskperception tasks and were more likely to be involved in road traffic accidents. [34][35][36] In view of this, a total of 40 female novice extroversion drivers were selected for eye movement data acquisition under calm and anxiety. The driving propensity of subjects is determined by Driving Propensity Questionnaire, 37 and the specific performance is shown in Table 3.…”

Section: Participantsmentioning

confidence: 99%

Analysis of female novice extroversion driver’s eye movement characteristics under anxiety

Liu

Wang

Liu

et al. 2019

Advances in Mechanical Engineering

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Anxiety is a common emotion of driver, which always affects the safety of driving. Eye movement characteristics can be used to understand the true emotion state of human beings. It is of great significance to study the law of eye movement for realizing active vehicle safety warning and human-machine cooperation. In this article, anxiety-induction experiment, real-vehicle driving experiments, and virtual driving experiments were designed and used to obtain the eye movement data of female novice extroversion driver under calm and anxiety, and mathematical statistics analysis was made on the fixation count, fixation duration, and visit duration in the area of interest within the driver horizon. The results showed that there are significant differences in fixation count and fixation duration of drivers (p\0:05, p is the accompanying probability), and the main effect of emotion is significant (p\0:05).Compared with the situation of calm, fixation area, fixation count, and fixation duration of drivers under anxiety were more focused on the middle area, the fixation count and visit duration on the left area were relatively more, the fixation duration on the right area was relatively longer, and anxiety was more likely to cause driver's attention bias.

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“…There have been a number of studies showing driver’s eye movement characteristics. Hills et al [20,21] found that driver’s eye movements change with the level of driving experience. It is not easy for novice drivers to apply appropriate eye-movement patterns to match the hazardousness of the road.…”

Section: Introductionmentioning

confidence: 99%

“…He et al [11] analyzed the effects of highway tunnel lighting environment on driving safety, using drivers’ eye movement parameters. Hills et al [20] explored the vertical eye-movement carryover from one task to a second task, and found that it is one potentially distracting effect on the safety of novice drivers. Oviedo-Trespalacios et al [26] conducted a systematic literature review to identify the impacts of roadside advertising signs on driver behavior and road safety.…”

Section: Introductionmentioning

confidence: 99%

Change-Point Analysis of Eye Movement Characteristics for Female Drivers in Anxiety

Guo

Wang

et al. 2019

IJERPH

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Driver hazard perception is highly related to involvement in traffic accidents, and vision is the most important sense with which we perceive risk. Therefore, it is of great significance to explore the characteristics of drivers’ eye movements to promote road safety. This study focuses on analyzing the changes of drivers’ eye-movement characteristics in anxiety. We used various materials to induce drivers’ anxiety, and then conducted the real driving experiments and driving simulations to collect drivers’ eye-movement data. Then, we compared the differences between calm and anxiety on drivers’ eye-movement characteristics, in order to extract the key eye-movement features. The least squares method of change point analysis was carried out to detect the time and locations of sudden changes in eye movement characteristics. The results show that the least squares method is effective for identifying eye-movement changes of female drivers in anxiety. It was also found that changes in road environments could cause a significant increase in fixation count and fixation duration for female drivers, such as in scenes with traffic accidents or sharp curves. The findings of this study can be used to recognize unexpected events in road environment and improve the geometric design of curved roads. This study can also be used to develop active driving warning systems and intelligent human–machine interactions in vehicles. This study would be of great theoretical significance and application value for improving road traffic safety.

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Detrimental effects of carryover of eye movement behaviour on hazard perception accuracy: Effects of driver experience, difficulty of task, and hazardousness of road

Cited by 25 publications

References 51 publications

Study on drivers' visual perception characteristics during the take‐over of vehicle control in automated driving

Study on drivers' visual perception characteristics during the take‐over of vehicle control in automated driving

Analysis of female novice extroversion driver’s eye movement characteristics under anxiety

Change-Point Analysis of Eye Movement Characteristics for Female Drivers in Anxiety

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