Physiological Measures of Risk Perception in Highly Automated Driving

Highly automated driving will likely result in drivers being out-of-the-loop during specific scenarios and engaging a wide range of non-driving related tasks. Manifesting lower levels risk perception to emerging events, thus affect drivers’ availability take-over manual control safety-critical scenarios. In this empirical research, we measured (N = 20) with cardiac skin conductance indicators through series high-fidelity, simulated highly By manipulating the presence surrounding traffic changing conditions as long-term modulators, including hazard event short-term modulator, hypothesised that an increase would induce greater physiological arousal. Our results demonstrate heart rate variability features are superior at capturing arousal variations from these long-term, low moderate contrast, responses more sensitive rapidly evolving situations associated high risk. Based on future driver state monitoring systems should adopt multiple measures capture changes long short term, modulation perception. This enable enhanced readiness improved safely deal events when requested by vehicle.