Improving Human-Autonomous Car Interaction Through Gaze Following Behaviors of Driving Agents

Abstract

Autonomous cars have been gaining attention as a future transportation option due to an envisioning of a reduction in human errors and achieving a safer, more energy efficient and more comfortable mode of transportation. However, eliminating human involvement may impact the usage of autonomous cars negatively because of the impairment of perceived safety and enjoyment of driving. In order to achieve a reliable interaction between an autonomous car and a human operator, the car should evince intersubjectivity, implying that it possesses the same intentions with as those of the human operator. One critical social cue for human to understand the intentions of others is eye gaze behaviours. This paper proposes an interaction method that utilizes the eye gazing behaviours of an in-car driving agent platform that reflects the intentions of a simulated autonomous car that holds a potential of enabling the human operators to perceive the autonomous car as a social entity. We conducted a preliminary experiment to investigate whether an autonomous car will be perceived as possessing the same intentions as a human operator through gaze following behaviors of the driving agents as compared to the conditions of random gazing as well as not using the driving agents at all. The results revealed that gaze-following behavior of the driving agents induces an increase in the perception of the intersubjectivity. Furthermore, a detailed eye gaze data analysis remarked that the gaze following behaviors of the robots received more attention from the driver. Finally, the proposed interaction method demonstrated that the autonomous system was perceived as safer and more enjoyable.