How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study.

Area of Science:

• Neuroscience
• Human-Computer Interaction
• Transportation Safety

Background:

• Driver risk perception is crucial for manual driving but poorly understood in automated driving contexts.
• Functional near-infrared spectroscopy (fNIRS) offers a potential novel method for assessing driver states and risk perception.

Purpose of the Study:

• To investigate the use of brain haemodynamic responses via fNIRS to measure perceived risk from traffic complexity during automated driving.
• To establish fNIRS as a viable tool for assessing driver risk perception in automated driving scenarios.

Main Methods:

• An empirical driving simulator experiment involving 23 volunteers under automated driving conditions.
• Varied traffic complexity in suburban and urban scenarios, including an unexpected hazardous event.
• Measured perceived risk using fNIRS (prefrontal cortical haemoglobin oxygenation) and self-reports.

Main Results:

• Significant increases in prefrontal cortical haemoglobin oxygenation were observed.
• These increases correlated with self-reported perceived risk and traffic complexity.
• Both fNIRS signals and self-reports showed heightened responses during the hazardous scenario.

Conclusions:

• fNIRS is a valuable tool for measuring perceived risk variations during highly automated driving.
• Drivers perceive moderate risk with increasing traffic complexity, even with automated systems, reflected in physiological responses.
• Future research can leverage fNIRS to understand risk assessment and its impact on driving behavior for safer automated driving adoption.