Cooperative Autonomous Driving: A Mirror Neuron Inspired Intention Awareness and Cooperative Perception Approach

Abstract

In this article, we present the concept of cooperative autonomous driving using mirror neuron inspired intention awareness and cooperative perception, whose primary benefit is to enable cooperative autonomous driving in a more general approach rather than complicated rule-based approaches. The cooperative perception can provide information on the upcoming traffic situations ahead, even beyond line-of-sight and field-of-view. From a control perspective, a spatial map for navigation planning is extended up to the boundary of connected vehicles in a see-through manner. By leveraging this augmented perception capability, a better driving decision can be accomplished in terms of traffic flow efficiency and safety improvement. For this purpose, we propose a mirror neuron inspired intention awareness algorithm along with planning and control methods for cooperative autonomous driving. We demonstrate the feasibility of our proposals through simulations and experiments on the road with a cooperative lane changing scenario.