Using Electroencephalography and Structured Data Collection Techniques to Measure Passenger Emotional Response in Human-Autonomous Vehicle Interactions

Wide spread consumer adoption of self-driving cars (SDC) is predicated on a level
of trust between humans and the autonomous vehicle. Despite advances being made
in the technical abilities of SDCs, recent studies indicate that people are negatively
predisposed toward utilizing autonomous vehicles. To bridge the gap between consumer
skepticism and adoption of SDCs, research is needed to better understand the
evolution of trust between humans and growing autonomous technologies. The question
of mainstream acceptance and requisite trust is explored through integration
of virtual reality SDC simulator, an electroencephalographic (EEG) recorder, and a
new approach for real-time trust measurement between passengers and SDCs. An
experiment on fifty human subjects was conducted where participants were exposed
to scenarios designed to induce positive and negative trust responses. Emotional state
was quantified by the EEG beta wave to alpha wave power ratio, and participants
self-reported their levels of trust in the SDC after each segment.