Gaze-Based Vehicle Driving Evaluation of System with an Actual Vehicle at an Intersection with a Traffic Light

Abstract

Due to the population aging in Japan, more elderly people are retaining their driver’s licenses and the increase in the number of car accidents by elderly drivers is a social problem. To address this problem, an objective data-based method to evaluate whether elderly drivers can continue driving is needed. In this paper, we propose a car driving evaluation system based on gaze as calculated by eye and head angles. We used an eye tracking device (TalkEye Lite) made by the Takei Scientific Instruments Cooperation. For our image processing technique, we propose a gaze fixation condition using deep learning (YOLOv2-tiny). By using an eye tracking device and the proposed gaze fixation condition, we built a system where drivers could be evaluated during actual car operation. We describe our system in this paper. In order to evaluate our proposed method, we conducted experiments from November 2017 to November 2018 where elderly people were evaluated by our system while driving an actual car. The subjects were 22 general drivers (two were 80–89 years old, four were 70–79 years old, six were 60–69 years old, three were 50–59 years old, five were 40–49 years old and two were 30–39 years old). We compared the subjects’ gaze information with the subjective evaluation by a professional driving instructor. As a result, we confirm that the subjects’ gaze information is related to the subjective evaluation by the instructor.