Detection and response to critical lead vehicle deceleration events with peripheral vision: Glance response times are independent of visual eccentricity

Svärd, Malin; Bärgman, Jonas; Victor, Trent

doi:10.1016/j.aap.2020.105853

Cited by 16 publications

(3 citation statements)

References 50 publications

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“…Also, the driving scene was occluded completely. In actual driving, drivers may still extract valuable cues from the environment using peripheral vision ( Lamble et al, 1999 ; Summala et al, 1998 ; Svärd et al, 2020 ; Terry et al, 2008 ), a topic studied by Senders himself in the context of distributed attention ( Senders et al, 1955 ). Future research could include other combinations of independent variables, such as occlusion combined with brake lights, a wider range of occlusion durations, and different occlusion triggers (e.g., automatic triggering vs. triggered by the driver; Lansdown et al, 2004 ).…”

Section: Discussionmentioning

confidence: 99%

The effect of an occlusion-induced delay on braking behavior in critical situations: A driving simulator study

Winter

Saffarian

Senders³

2022

Hum Factors

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Objective To share results of an experiment that used visual occlusion for a new purpose: inducing a waiting time. Background Senders was a leading figure in human factors. In his research on the visual demands of driving, he used occlusion techniques. Methods In a simulator experiment, we examined how drivers brake for different levels of urgency and different visual conditions. In three blocks (1 = brake lights, 2 = no brake lights, 3 = occlusion), drivers followed a vehicle at 13.4 or 33.4 m distance. At certain moments, the lead vehicle decelerated moderately (1.7 m/s2) or strongly (6.5 m/s2). In the occlusion condition, the screens blanked for 0.4 s (if 6.5 m/s2) or 2.0 s (if 1.7 m/s2) when the lead vehicle started to decelerate. Participants were instructed to brake only after the occlusion ended. Results The lack of brake lights caused a delayed response. In the occlusion condition, drivers adapted to the instructed late braking by braking harder. However, adaptation was not always possible: In the most urgent condition, most participants collided with the lead vehicle because the ego-vehicle’s deceleration limits were reached. In non-urgent conditions, some drivers braked unnecessarily hard. Furthermore, while waiting until the occlusion cleared, some drivers lightly touched the brake pedal. Conclusion This experimental design demonstrates how drivers (sometimes fail to) adjust their braking behavior to the criticality of the situation. Application The phenomena of biomechanical readiness and (inappropriate) dosing of the brake pedal may be relevant to safety, traffic flow, and ADAS design.

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Section: Discussionmentioning

confidence: 99%

The effect of an occlusion-induced delay on braking behavior in critical situations: A driving simulator study

Winter

Saffarian

Senders³

2022

Hum Factors

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“…Feature importance analyses from the reviewed studies identified blink frequency, eyelid movement, gaze eccentricity (measured from the road center), gaze location, gaze duration, head movement, saccade magnitude, blink duration, pupil size, and the spatial distribution of the gaze pattern as important features. Gaze location was the most frequently identified important feature followed by blink frequency, glance duration, and spatial distribution of the gaze pattern (Costela & Castro-Torres, 2020;Liang et al, 2021;Mulhall et al, 2020;Svärd et al, 2021;Wu et al, 2021).…”

Section: Eye-tracking and Head Measuresmentioning

confidence: 99%

A review of best practices, standards, and approaches for transportation safety data and driver state prediction

Nartey,

Alambeigi,

McDonald

et al. 2023

Proceedings of the Human Factors and Ergonomics Society Annual

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This systematic review documents current best practices, standards, and approaches for transportation safety data analytics. While standards exist for defining measures, there are few available standards or guides for processing driving and driver data. Standards are crucial for ensuring repeatability and appropriate cost-benefit decisions. The review identified 36 relevant studies describing behavioral and physiological measures. Most studies do not comprehensively report data processing steps. Of the studies that did report data processing steps, few analyzed the impact of decisions made during data processing on algorithm performance. Most studies were conducted in a controlled simulator environment and may not generalize to naturalistic settings. The findings show that driver behavior and physiological data show efficacy for detecting fatigue, distraction, stress, and driver errors. The results of these studies may necessitate additional data processing standards and future work should focus on measuring the effects of data decisions on model performance.

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“…Using a manual driving simulator study, ref. [7] found that engaging in a self-paced, visual-manual tracking task with high visual eccentricity (60 degrees) still allowed drivers sufficient on-road glances, suggesting that drivers use peripheral vision to collect evidence for braking during off-road glances.…”

Section: Introductionmentioning

confidence: 99%

Is Users’ Trust during Automated Driving Different When Using an Ambient Light HMI, Compared to an Auditory HMI?

et al. 2023

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The aim of this study was to compare the success of two different Human Machine Interfaces (HMIs) in attracting drivers’ attention when they were engaged in a Non-Driving-Related Task (NDRT) during SAE Level 3 driving. We also assessed the value of each on drivers’ perceived safety and trust. A driving simulator experiment was used to investigate drivers’ response to a non-safety-critical transition of control and five cut-in events (one hard; deceleration of 2.4 m/s2, and 4 subtle; deceleration of ~1.16 m/s2) over the course of the automated drive. The experiment used two types of HMI to trigger a takeover request (TOR): one Light-band display that flashed whenever the drivers needed to takeover control; and one auditory warning. Results showed that drivers’ levels of trust in automation were similar for both HMI conditions, in all scenarios, except during a hard cut-in event. Regarding the HMI’s capabilities to support a takeover process, the study found no differences in drivers’ takeover performance or overall gaze distribution. However, with the Light-band HMI, drivers were more likely to focus their attention to the road centre first after a takeover request. Although a high proportion of glances towards the dashboard of the vehicle was seen for both HMIs during the takeover process, the value of these ambient lighting signals for conveying automation status and takeover messages may be useful to help drivers direct their visual attention to the most suitable area after a takeover, such as the forward roadway.

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Detection and response to critical lead vehicle deceleration events with peripheral vision: Glance response times are independent of visual eccentricity

Cited by 16 publications

References 50 publications

The effect of an occlusion-induced delay on braking behavior in critical situations: A driving simulator study

The effect of an occlusion-induced delay on braking behavior in critical situations: A driving simulator study

A review of best practices, standards, and approaches for transportation safety data and driver state prediction

Is Users’ Trust during Automated Driving Different When Using an Ambient Light HMI, Compared to an Auditory HMI?

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