Estimation of Drivers’ Gaze Behavior by Potential Attention When Using Human–Machine Interface - Yu Yamaguchi; Yuki Okafuji; Takahiro Wada; Kazuomi Murakami; Hiroyuki Ishida (IEEE Access, 2023)
Recently, various visual information presentation systems known as human–machine interfaces (HMIs), such as road projection lamp systems, have been developed for safe driving. However, it is unclear how these HMIs change the drivers’ gaze behavior and improve their cognitive awareness of the environment. Therefore, in this study, we introduce the concept of potential attention to propose a probabilistic method to estimate drivers’ gaze behavior when using HMIs. The potential attention hypothesis can propose an explanation to understand gaze behavior. This method assigns potential attention to objects the driver is likely to gaze, such as vehicles and pedestrians, thereby estimating the driver’s potential gaze point from potential attentions. The study is divided into two steps. The first step analyzes the drivers’ gaze behavior in the simulator experiment when a road projection lamp is displayed to alert pedestrians. In the second step, we propose a method for estimating the driver’s gaze through the potential attention method based on the results of the simulator experiment. The modeling results for gaze behavior measured in the simulator experiment as the first step show that gaze behavior can be estimated with high accuracy. This proposed method is expected to apply to a method to determine where the HMI display should be placed.