Integrated Sensing and Communication in Obstacle Avoidance System for Autonomous Vehicles

To address the problem of autonomous vehicles in terms of sensing distance, reaction time and recognition accuracy, this paper proposes a collective control method for autonomous vehicles. We design a model of autonomous vehicle traffic system featuring sensing and communication integration. This system achieves collective vehicle movement and collaborative obstacle avoidance through the perception and judgment of the surrounding environmental conditions by the fleet of autonomous vehicles. We propose a new clustering algorithm called Low Energy Adaptive Clustering Hierarchy - Fleet (LEACH-F), based on classical LEACH algorithm. This algorithm is adapted for autonomous vehicles to realize node clustering and routing in sensing and communication network. In this paper, we also optimize the Re-architecting congestion control (PCC) algorithm to adapt the fleet of autonomous vehicles, which enhances the forwarding efficiency in the communication links.