Conflict Resolution at High Traffic Densities with Reinforcement Learning

Increasing delays and congestion reported in many aviation sectors indicate that the current centralised operational model is rapidly approaching saturation levels. Air Traffic Control (ATC) system is not expected to keep pace with the ever-increasing demand for air transportation. Its capacity is still limited by the available controllers, and...

Urban Air Traffic Management For Collision Avoidance with Non-Cooperative Airspace Users

With the rise of new and innovative Urban Air Mobility solutions, there also arises a need to integrate these into the existing airspace. Current airspace users include conventional civil, commercial and general aviation, military air users, police and emergency services as well as a plethora of avian life. Planned additions to the airspace are...

Using Reinforcement Learning to Improve Airspace Structuring in an Urban Environment

Current predictions on future drone operations estimate that traffic density orders of magnitude will be higher than any observed in manned aviation. Such densities redirect the focus towards elements that can decrease conflict rate and severity, with special emphasis on airspace structures, an element that has been overlooked within...

Using Reinforcement Learning in a Layered Airspace to Improve Layer Change Decision

Current predictions for future operations with drones estimate traffic densities orders of magnitude higher than any observed in manned aviation. Such densities call for further research and innovation, in particular, into conflict detection and resolution without the need for human intervention. The layered airspace concept, where aircraft...

Improving Safety of Vertical Manoeuvres in a Layered Airspace with Deep Reinforcement Learning

Current estimates show that the presence of unmanned aviation is likely to grow exponentially over the course of the next decades. Even with the more conservative estimates, these expected high traffic densities require a re-evaluation of the airspace structure to ensure safe and efficient operations. One structure that scored high on both the...

Distributed Conflict Resolution at High Traffic Densities with Reinforcement Learning

Future operations involving drones are expected to result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Current geometric conflict resolution (CR) methods have proven to be very efficient at relatively moderate densities. However, at higher densities, performance is hindered by the...

Velocity Obstacle Based Conflict Avoidance in Urban Environment with Variable Speed Limit

Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in conflict detection and resolution (CD&R) methods. The use of drones for applications such as package delivery, would result in traffic densities that are orders of magnitude higher than those currently...

Limitations of Conflict Prevention and Resolution in Constrained Very Low-Level Urban Airspace

Road traffic delay and urban overcrowding are increasing rapidly all over the world. As a result, several companies have proposed the use of small unmanned aerial vehicles (sUAVs) as an alternative to road-based transportation. These small autonomous drones are expected to operate within a thin airspace band (Very Low Level) in high traffic...

Safety Optimization of a Layered Airspace Structure with Supervised Learning

The capacity of the current system of air traffic is rapidly reaching a limit with the increasing demand for air transportation. Expected future traffic densities not only make automated conflict detection and resolution a necessity, but also force a re-evaluation of coordination elements to decrease conflict rate and severity. It has been...

Review of conflict resolution methods for manned and unmanned aviation

Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in Conflict Detection and Resolution (CD&R) methods. With the new applications of drones, and the implications of a profoundly different urban airspace, new demands are placed on such algorithms, further...

Determining Optimal Conflict Avoidance Manoeuvres At High Densities With Reinforcement Learning

The use of drones for applications such as package delivery, in an urban setting, would result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Current geometric resolution models have proven to be very efficient at relatively moderate densities. However, at higher densities, performance is hindered...

Improvement of Conflict Detection and Resolution at High Densities Through Reinforcement Learning

The use of drones for applications such as package delivery, in an urban setting, would result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Current geometric resolution models have proven to be very efficient. However, at the extreme densities envisioned for such drone applications, performance...

The Effect of Intent on Conflict Detection and Resolution at High Traffic Densities

The use of drones for applications such as package delivery, in an urban setting, would result in traffic densities that are orders of magnitude higher than any observed in manned aviation. Such densities not only make automated conflict detection and resolution a necessity, but it will also force a reevaluation of aspects such as centralised vs...

Analysis of Conflict Resolution Methods for Manned and Unmanned Aviation Using Fast-Time Simulations

In the coming years, aviation will have to cope with an increase in the number of aircraft, and of drones purchased in the open market. The human intervention of Air Traffic Management (ATM) will be overburden with guaranteeing flight safety with hundreds of manned aircraft and Unmanned Aerial Vehicles (UAVs) operating simultaneously. Conflict...