Automatic Driving Experiment of a Personal Vehicle Using Detection of Steady-State Visual Evoked Potentials by Measurement Objects in Mixed Reality

Abstract

With the aging population, personal vehicles (PVs) have become widely used and are important mobility devices for the elderly. Driving a PV for the elderly involves risks such as collisions. Therefore, driving assistance and a training system utilizing mixed reality (MR) have been developed. However, as these systems are controlled manually, safe operation cannot be guaranteed, particularly for users who are not good at operating them. In this study, an autonomous driving system for a PV using a brain-computer interface is proposed. Measurement objects generating flicker stimuli are projected onto the MR device, and steady-state visual evoked potentials in the visual cortex are detected. Using the automatic driving system, safe operation is realized without stopping, as the intention of the traveling direction of the PV is estimated. The effectiveness of the proposed system is demonstrated through experiments, and the driving workloads are evaluated using NASA-TLX.