Using Smartbands, Pupillometry and Body Motion to Detect Discomfort in Automated Driving

Abstract

As technological advances lead to rapid progress in driving automation, human-machine interaction (HMI) issues such as comfort in automated driving gain increasing attention. The research project KomfoPilot at Chemnitz University of Technology aims to assess discomfort in automated driving using physiological parameters from commercially available smartbands, pupillometry and body motion. Detected discomfort should subsequently be used to adapt driving parameters as well as information presentation and prevent potentially safety-critical take-over situations. In an empirical driving simulator study, 40 participants from 25 years to 84 years old experienced two highly automated drives with three potentially critical and discomfort-inducing approaching situations in each trip. The ego car drove in a highly automated mode at 100 km/h and approached a truck driving ahead with a constant speed of 80 km/h. Automated braking started very late at a distance of 9 m, reaching a minimum of 4.2 m. Perceived discomfort was assessed continuously using a handset control. Physiological parameters were measured by the smartband Microsoft Band 2 and included heart rate (HR), heart rate variability (HRV) and skin conductance level (SCL). Eye tracking glasses recorded pupil diameter and eye blink frequency; body motion was captured by a motion tracking system and a seat pressure mat. Trends of all parameters were analyzed 10 s before, during and 10 s after reported discomfort to check for overall parameter relevance, direction and strength of effects; timings of increase/decrease; variability as well as filtering, standardization and artifact removal strategies to increase the signal-to-noise ratio. Results showed a reduced eye blink rate during discomfort as well as pupil dilation, also after correcting for ambient light influence. Contrary to expectations, HR decreased significantly during discomfort periods, whereas HRV diminished as expected. No effects could be observed for SCL. Body motion showed the expected pushback movement during the close approach situation. Overall, besides SCL, all other parameters showed changes associated with discomfort indicated by the handset control. The results serve as a basis for designing and configuring a real-time discomfort detection algorithm that will be implemented in the driving simulator and validated in subsequent studies.

How Long Does It Take to Relax? Observation of Driver Behavior During Real-World Conditionally Automated Driving

“…Seating position. A higher shoulder level and head position (z-axis) is considered to indicate stress and discomfort (Beggiato, Hartwich & Krems, 2018;Tran & Trivedi, 2010). The driver's foot on or hovering over the brake pedal indicates that the driver feels a need to be ready to take over the maneuvering control (Andersson et al, 2018).…”

MEYE: Web-app for translational and real-time pupillometry

“…CC-BY-NC 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted March 10, 2021. ; https://doi.org/10.1101/2021.03.09.434438 doi: bioRxiv preprint facilitate Human-Computer Interaction in normal subjects [28][29][30] and patients with severe motor disabilities. For example, pupil dynamics is used to assess communication capability in Locked-in Syndrome, a crucial factor for the determination of a minimally conscious state [31,32].…”

“…A growing body of work shows how pupillometry can be used as a possible biomarker for numerous neurological and psychiatric conditions in early development and adult subjects [13–27]. Spontaneous and voluntary modulation of pupil fluctuations have also been used to facilitate Human-Computer Interaction in normal subjects [28–30] and patients with severe motor disabilities. For example, pupil dynamics is used to assess communication capability in Locked-in Syndrome, a crucial factor for the determination of a minimally conscious state [31,32].…”

Proposal of Relative Thermal Sensation: Another Dimension of Thermal Comfort and Its Investigation

“…However, the PMV/PPD method lacks the ability to account for individual differences. Physiological factors, including local body temperatures [10]- [13], heart rate variability (HRV) [14]- [17], pupil dilation [18], [19], et cetera, have been proved to have substantial impacts on thermal comfort, which are essential in establishing personalized thermal comfort models. Nowadays, with the rapid developing speed of technology, physiological measurement is becoming easier and easier, and the cost is becoming lower and lower.…”