Industrial and Operations Engineering, University of Michigan
Psychophysiological responses to takeover requests in conditionally automated driving
In SAE Level 3 automated driving, taking over control from automation raises significant safety concerns because drivers out of the vehicle control loop have difficulty negotiating takeover transitions. Existing studies on takeover transitions have focused on drivers’ behavioral responses to takeover requests (TORs). As a complement, this exploratory study aimed to examine drivers’ psychophysiological responses to TORs as a result of varying non-driving-related tasks (NDRTs), traffic density and TOR lead time. A total number of 102 drivers were recruited and each of them experienced 8 takeover events in a high fidelity fixed-base driving simulator. Drivers’ gaze behaviors, heart rate (HR) activities, galvanic skin responses (GSRs), and facial expressions were recorded and analyzed during two stages.
First, during the automated driving stage, we found that drivers had lower heart rate variability, narrower horizontal gaze dispersion, and shorter eyes-on-road time when they had a high level of cognitive load relative to a low level of cognitive load. Second, during the takeover transition stage, 4s lead time led to inhibited blink numbers and larger maximum and mean GSR phasic activation compared to 7s lead time, whilst heavy traffic density resulted in increased HR acceleration patterns than light traffic density. Our results showed that psychophysiological measures can indicate specific internal states of drivers, including their workload, emotions, attention, and situation awareness in a continuous, non-invasive and real-time manner. The findings provide additional support for the value of using psychophysiological measures in automated driving and for future applications in driver monitoring systems and adaptive alert systems.
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This simulator was equipped with a Smart Eye four-camera eye-tracking system (Smart Eye, Sweden) that provided live head-pose, eye-blink, and gaze data. The sampling rate of the eye-tracking system was 120 Hz. The Shimmer3 GSR+unit including GSR electrodes and photoplethysmographic (PPG) probe was used to collect GSR and HR data with a sampling rate of 128 Hz. A Logitech web camera with a sampling rate of 30Hz was used to collect drivers’ facial expressions. The iMotions software was used for psychophysiological data synchronization and visualization in real time.
Keywords: Human-automation interaction, Automated driving, Transition of control, Psychophysiological measures.