View article

Urban Air Mobility (UAM) is an emergent concept for future air transportation. With UAM, cargo and passengers will be transported on-demand in urban airspace. UAM has shown a promising prospect in mitigating ground congestion and providing people with an alternative mobility option. However, unauthorized unmanned aerial vehicles (UAVs) in urban airspace present a significant threat to safety of UAM, drawing significant attention from research communities recently. Among all solutions, cooperative pursuit using a team of UAVs is an effective countermeasure for unauthorized UAVs in urban airspace. In this paper, we model cooperative pursuit as a pursuit-evasion game problem (PEG) and propose a multi-agent reinforcement learning (MARL) based approach to solve the problem efficiently. The proposed approach incorporates novel cellular-enabled parameter sharing and curriculum learning schemes to …