2019
DOI: 10.1177/0018720819850283
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Moving Into the Loop: An Investigation of Drivers’ Steering Behavior in Highly Automated Vehicles

Abstract: Objective This paper investigates driver engagement with vehicle automation and the transition to manual control in the context of a phenomenon that we have termed vicarious steering—drivers steering when the vehicle is under automated control. Background Automated vehicles introduce many challenges, including disengagement from the driving task and out-of-the-loop performance decrement. We examine drivers’ steering behavior when the automation is engaged, and steering input has no effect on the vehicle state.… Show more

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Cited by 18 publications
(9 citation statements)
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“…Therefore, it is important to assess the drivers' visual attention and takeover readiness before the initiation of TORs. There is a proven high correlation between a driver's visual attention and eye movement [1,63,64]. DeepTake uses eye movement data (e.g., gaze position, fixation duration on areas of interest) measured by eye-tracker devices.…”
Section: Multimodal Data Sourcesmentioning
confidence: 99%
See 1 more Smart Citation
“…Therefore, it is important to assess the drivers' visual attention and takeover readiness before the initiation of TORs. There is a proven high correlation between a driver's visual attention and eye movement [1,63,64]. DeepTake uses eye movement data (e.g., gaze position, fixation duration on areas of interest) measured by eye-tracker devices.…”
Section: Multimodal Data Sourcesmentioning
confidence: 99%
“…The main contribution of this work is the development of Deep-Take framework that predicts driver takeover intention, time and quality using vehicle data, driver biometrics and subjective measurements 1 . The intersection between ubiquitous computing, sensing and emerging technologies offers promising avenues for DeepTake to integrate modalities into a novel human-centered framework to increase the robustness of drivers' takeover behavior prediction.…”
Section: Introductionmentioning
confidence: 99%
“…They found that drivers had an increased SDLP and decreased mean Time to Collision (TTC) after system withdrawal. Alsaid et al (2020) investigated drivers' vicarious steering behavior (steering behavior before transitions) when the automated system is fully engaged. They evaluated the relationship between vicarious steering and the quality of transitions.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Participants were instructed to show their dissatisfaction with the driving style of the automation with the brake and accelerator pedals. This pedal input measure builds on previous research that shows that riders’ steering input when the vehicle is under automated control indicates engagement and a propensity to take back control (Alsaid, Lee, & Price, 2019). More generally, the propensity to intervene provides a behavioral indicator of trust in automation (Meyer & Lee, 2013), which has been defined as “.…”
Section: Introductionmentioning
confidence: 97%