33 citations · 124 across the 19 of their papers we have counts for
19 papers
Safe and Scalable Real-Time Trajectory Planning Framework for Urban Air Mobility
Abenezer Taye, Roberto Valenti, Akshay Rajhans +3
This paper presents a real-time trajectory planning framework for Urban Air Mobility (UAM) that is both safe and scalable. The proposed framework employs a decentralized, free-flig…
Integrated Conflict Management for UAM with Strategic Demand Capacity Balancing and Learning-based Tactical Deconfliction
Shulu Chen, Antony Evans, Marc Brittain +1
Urban air mobility (UAM) has the potential to revolutionize our daily transportation, offering rapid and efficient deliveries of passengers and cargo between dedicated locations wi…
One-Shot Strategically Deconflicted Route and Operational Volume Generation for Urban Air Mobility Operations
Ellis L Thompson, Yan Xu, Peng Wei
In the UAM space, strategic deconfliction provides an all-essential layer to airspace automation by providing safe, pre-emptive deconfliction or assignment of airspace resources to…
A Framework for Operational Volume Generation for Urban Air Mobility Strategic Deconfliction
Ellis Lee Thompson, Yan Xu, Peng Wei
Strategic pre-flight functions focus on the planning and deconfliction of routes for aircraft systems. The urban air mobility concept calls for higher levels of autonomy with onboa…
Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning
Jueming Hu, Xuxi Yang, Weichang Wang +3
Obstacle avoidance for small unmanned aircraft is vital for the safety of future urban air mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are man…
Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance
Wei Guo, Marc Brittain, Peng Wei
The separation assurance task will be extremely challenging for air traffic controllers in a complex and high density airspace environment. Deep reinforcement learning (DRL) was us…