Prefrontal Correlates of Passengers’ Mental Activity Based on fNIRS for High-Level Automated Vehicles

Abstract

With the spread adoption of artificial intelligence, the great challenges confronted by the intelligent safety concern-safety of the intended functionality has become the biggest roadblock to the mass production of high-level automated vehicles, notably arising from perception algorithm deficiencies. This paper focuses a cut-in scenario, dividing this scenario into low-risk and high-risk segments predicated on the kinetic energy field, and the mental activities of passengers on prefrontal cortex, are analyzed within these delineated segments. Two experiments are then conducted, leveraging driving simulators and real-world vehicles, respectively. Experiment results indicate that high risk may result in the passengers’ mental activity on prefrontal cortex change. This revelation posits a potential avenue for augmenting the intended functionality of automated vehicle by using passengers’ physiological state.