Abstract
Highly automated driving will likely result in drivers being out-of-the-loop during specific scenarios and engaging in a wide range of non-driving related tasks. Manifesting in lower levels of risk perception to emerging events, and thus affect drivers’ availability to take-over manual control in safety-critical scenarios. In this empirical research, we measured drivers’ (N = 20) risk perception with cardiac and skin conductance indicators through a series of high-fidelity, simulated highly automated driving scenarios. By manipulating the presence of surrounding traffic and changing driving conditions as long-term risk modulators, and including a driving hazard event as a short-term risk modulator, we hypothesised that an increase in risk perception would induce greater physiological arousal. Our results demonstrate that heart rate variability features are superior at capturing arousal variations from these long-term, low to moderate risk scenarios. In contrast, skin conductance responses are more sensitive to rapidly evolving situations associated with moderate to high risk. Based on this research, future driver state monitoring systems should adopt multiple physiological measures to capture changes in the long and short term, modulation of risk perception. This will enable enhanced perception of driver readiness and improved availability to safely deal with take-over events when requested by an automated vehicle.
Highlights
D URING Highly Automated Driving (HAD) (i.e. SAE Levels 3 and 4) [1], drivers will not be required to monitor or engage in the driving task during predefined use cases
Arousal levels will be critical to informing the driver state monitoring (DSM) system of the current OOTL state, which will depend on the nature of the ongoing non-driving related tasks (NDRTs) and each individual
Our empirical research provided evidence on how heart rate (HRV) and skin conductance (SCR) features provide valuable additional realtime data to determine drivers’ perceived risk, which can be used to indicate their availability to take over control
Summary
D URING Highly Automated Driving (HAD) (i.e. SAE Levels 3 and 4) [1], drivers will not be required to monitor or engage in the driving task during predefined use cases. For drivers waking from a nap, the transition from sleep to wakefulness is characterised by “hypovigilance, confusion, disorientation of behaviour, and impaired cognitive and sensory-motor performance” [25], and drivers in such a state would likely be impaired for taking over manual control. Another case could be those drivers that have been engaged in a mentally demanding task (e.g. playing video games, on a phone call or a videoconference). Is where multimodal DSM systems, relying on psychophysiological measures, could determine driver readiness
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More From: IEEE Transactions on Intelligent Transportation Systems
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