Learning to Navigate Connected Autonomous Cars for Long-Term Communication Coverage

摘要

Autonomous cars employed as mobile base stations could provide communication networks in network-congested areas. In this paper, the authors leverage emerging deep reinforcement learning (DRL) techniques for enabling autonomous cars control and present a novel and highly effective DRL-based control framework called DRL-C3.