Driving Characteristics when Autonomous Driving Change to Driver in Low Alertness and Awake from Sleeping

Gokan, Masato; Yamaguchi, Daisuke; Hirose, Toshiya

doi:10.4271/2018-01-1081

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…People's trust in this type of technology may vary [21] [22]-drivers with low levels of trust may remain in an unpleasant, tense state from the point of relinquishing control right up until the point of regaining control of their vehicle. This situation is not ideal as the experience of stress can impair drivers' ability to retrieve control from the automated system [23] [24], may cause non-optimal manual driving performance, and may even result in a reduced tendency to engage with the assisted system in the future.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Unimodal and Multimodal Measurements of Driver Stress in Real-World Driving Conditions

Spencer¹,

Ia²,

Suga³

et al. 2020

Preprint

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Objectively measuring drivers’ emotions in real-world conditions is a challenging endeavour. This study investigated whether drivers’ emotional responses were captured more meaningfully by unimodal measurements or by a multimodal machine-learning approach. Ten participants drove a 23-mile route around Sunnyvale, California, while their heart rate, breathing rate and facial expressions were recorded. At regular intervals, participants indicated how they were feeling. After the study, independent observers reviewed a sample of the videotaped sessions, classifying the participants as experiencing high or low levels of stress according to their behaviour. The degree to which drivers’ self-report scores, single physiological data streams and facial behaviour - as judged by a facial recognition machine classifier - reflected their actual stress levels was compared to the multimodal algorithmic estimates which combined physiological and facial data outputs. The results showed that, compared to the other single data modes, the multimodal approach captured how the participants were feeling in a way which most meaningfully corresponded with their observed behaviour. The findings re-affirm the need for multimodal emotion-recognition systems for capturing driver stress. The limitations of the study are also discussed.

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Section: Introductionmentioning

confidence: 99%