A Study on the Driver-Vehicle Interaction System in Autonomous Vehicles Considering Driver’s Attention Status

Before fully autonomous driving technology is developed, drivers are not free from the responsibility of Take-Over Request (TOR). Even with level 5 automation, a driver still can play a role as a final decision maker for various driving and non-driving functions, even though most of the tasks will be conducted by the vehicle. In this regard, the performance of the driver’s reaction to the request from the car is crucial in autonomous driving throughout and it is highly dependent on the driver’s attention. It is important to understand the state of the driver during autonomous driving and utilize this information in the driver-vehicle interaction system to enhance safety. Accordingly, it is important to extract features from information about the driver and the surrounding environment in order to increase the accuracy of the model that predicts the driver’s state. This paper aims to examine a method of predicting an attentional status based on the driver’s emotional state and explore the possibility of applying brain-computer interaction (BCI) with consideration of the driver’s type to increase accuracy. As a result, the prediction model for attentional state with emotional information was developed, and the driver’s characteristics and types were investigated. Based on the results, a driver-vehicle interaction system was proposed for the context of the autonomous vehicle in the future. Although the prediction model for attentional status was not powerful, it can be developed by considering more critical features such as driver’s characteristics and types. In addition, it can be used as a constraint for effective interaction when a driver uses the BCI system to deliver his/her decision to a vehicle.