Interactive cognition in self-driving

Abstract

In recent years, self-driving approaches, such as Tesla, Waymo, and Intel, have focused on computational awareness, including cognitive perception, planning, and decision making. However, little effort has been concentrated on interactive cognition. This problem is important for unmanned vehicles to be accepted by society. Targeting on this urgent issue, we analyze the richness and difficulties of the interactive cognition of self-driving vehicles. The interactive cognition of self-driving can be divided into the vehicle intelligent speaker dialogue based on natural language interaction, body language interaction, and vehicle body language interaction. Through the interactive cognition of self-driving, it can employ intelligent speakers and the Internet to achieve the interaction between self-driving vehicles and owners, crews, operation and maintenance personnel, developers, remote service requests, etc. This paper solves the gesture recognition and understanding of pedestrians and road traffic police, and also overcomes two typical body interaction problems, including the car-meeting task at narrow roads and the car overtaking/merging task. Finally, based on many self-driving interactive cognitions, we provide an interactive bus architecture that is independent of a decision bus, and apply it in various types of smart cars.