Learning analysis of obstacle avoidance to beginners at trial times using NASA-TLX for drive assist system of welfare vehicle using Mixed Reality

Abstract

Recently, welfare vehicles are widely used among the aged. However, it is not easy for inexperienced beginners or the aged to control the welfare vehicle in the narrow place. For the problem, the driving assistance system was proposed in which a virtual vehicle is projected on head mounted display (HMD) and controlled by a third person viewpoint. However, as a user wears HMD to control the virtual vehicle, the driving situation of the virtual vehicle was not visible from outsiders and the appropriate guidance was not provided to beginners. In order to get the driving skill of the vehicle more quickly, it is important to utilized the mixed reality (MR) space using the virtual object and to provide timely guidance while checking the movements of the virtual vehicle. In this paper, we propose a drive assist system of welfare vehicle for beginners using Mixed Reality. A virtual course that automatically displays virtual objects using MR is constructed and the virtual space is shared with the instructor. To evaluate the practice of the driving skill for beginners, NASA task load index (NASA-TLX) is used for quantifying the mental work-load. As a result, proposed method suppresses the weighted workload (WWL) score, and it is clarified that the driving skill is improved in a smaller number of trials.

Keywords

• welfare vehicle
• virtual platoon
• mixed reality
• nasa-tlx
• wwl score
• driving skill