Psychophysiological responses to takeover requests in conditionally automated driving
URL: http://arxiv.org/abs/2010.03047v1
archive: archived pipeline: cataloged verified
Abstract
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.
Summary
Du, Yang, and Zhou recorded psychophysiological responses to takeover requests in SAE Level 3 simulated driving, with 102 drivers each experiencing 8 takeover events varying NDRT, traffic density, and TOR lead time. During automated driving, high cognitive load reduced heart-rate variability, narrowed horizontal gaze dispersion, and shortened eyes-on-road time; during the takeover transition, 4-second lead time produced inhibited blink counts and larger maximum/mean GSR phasic activation versus 7-second lead time, while heavy traffic raised HR-acceleration patterns relative to light traffic. The authors argue psychophysiological measures continuously index workload, attention, and situation awareness in ways that complement behavioral takeover metrics.
Key finding
Heart-rate variability, gaze dispersion, GSR, and blink measures tracked cognitive load and takeover-request lead-time/traffic-density manipulations, supporting psychophysiological monitoring as a complement to behavioral takeover metrics.
Methodology
High-fidelity fixed-base driving-simulator study with 102 drivers experiencing 8 takeover events each in SAE Level 3 conditional automation. Manipulated NDRTs, traffic density, and TOR lead time (4s vs 7s). Measured gaze behavior, heart rate (and HRV), galvanic skin response (phasic max/mean), and facial expressions during automated and takeover-transition stages.
Sample size: N=102
Quality score: 5 / 5