Passenger physiology in self-driving vehicles during unexpected events

Area of Science:

• Human-computer interaction
• Automotive engineering
• Cognitive psychology

Background:

• Fully autonomous vehicles (AVs) promise societal transformation but widespread adoption is limited.
• Passenger reactions to AVs, particularly during unexpected events, are not well understood.
• Prior research indicates lower anxiety in human-driven vs. self-driving conditions.

Purpose of the Study:

• To investigate passenger physiological responses to unexpected road events in both human-driven and self-driving modes.
• To compare passenger affective preferences between human-driven and autonomous driving scenarios.
• To assess the impact of unexpected events on physiological indicators of passenger experience.

Main Methods:

• Real-world driving experiment on a closed test track.
• Comparison of human-driven and self-driving modes with simulated unexpected obstacles (deer, dummies).
• Collection of physiological data: electroencephalography (EEG), eye movements, head movements, and blinking frequencies.

Main Results:

• Passengers exhibited moderate affective preferences for human-driven conditions over self-driving.
• Unexpected events led to wider multifractal spectra in eye and head movements.
• Blinking frequencies decreased during unexpected events in both driving conditions.

Conclusions:

• Real-world physiological measurements provide valuable insights into passenger experience with AVs.
• Findings suggest differences in passenger comfort and anxiety between human and autonomous driving, especially during critical events.
• Physiological data can inform the design and acceptance of self-driving technologies.