Related papers: Airspace-aware Contingency Landing Planning
Safety is a critical concern for urban flights of autonomous Unmanned Aerial Vehicles. In populated environments, risk should be accounted for to produce an effective and safe path, known as risk-aware path planning. Risk-aware path…
Air Navigation Service Providers (ANSP) worldwide have been making a considerable effort for the development of a better method to measure and predict aircraft counts within a particular airspace, also referred to as airspace density. An…
Autonomous mobile agents often operate in hazardous environments, necessitating an awareness of safety. These agents can have non-linear, stochastic dynamics that must be considered during planning to guarantee bounded risk. Most state of…
The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning. This study proposes a more dynamic airspace configuration (DAC) approach that could increase…
In this paper, we propose a conflict-free multi- agent flight scheduling that ensures robust separation in con- strained airspace for Urban Air Mobility (UAM) operations application. First, we introduce Pairwise Conflict Avoidance (PCA)…
This paper develops a high-density air corridor traffic flow model for Uncrewed Aircraft System (UAS) operation in urban low altitude airspace. To maximize throughput with safe separation guarantees, we define an airspace spatiotemporal…
Dynamic low altitude networks offer significant potential for efficient and reliable data transport via unmanned aerial vehicles (UAVs) relays which usually operate with predetermined trajectories. However, it is challenging to optimize the…
Under increasing economic and environmental pressure, airlines are constantly seeking new technologies and optimizing flight operations to reduce fuel consumption. However, the current practice on fuel loading, which has a significant…
Air traffic control is a real-time safety-critical decision making process in highly dynamic and stochastic environments. In today's aviation practice, a human air traffic controller monitors and directs many aircraft flying through its…
This paper addresses aircraft delays, emphasizing their impact on safety and financial losses. To mitigate these issues, an innovative machine learning (ML)-enhanced landing scheduling methodology is proposed, aiming to improve automation…
We investigate a method to deal with congestion of sectors and delays in the tactical phase of air traffic flow and capacity management. It relies on temporal objectives given for every point of the flight plans and shared among the…
We discuss surveillance with multiple unmanned aerial vehicles (UAV) that minimize idleness (the time between consecutive visits of sensing locations) and constrain latency (the time between capturing data at a sensing location and its…
This paper presents a method for generating probabilistic descent trajectories in simulations of real-world airspace. A dataset of 116,066 trajectories harvested from Mode S radar returns in UK airspace was used to train and test the model.…
Loss of thrust emergencies-e.g., induced by bird/drone strikes or fuel exhaustion-create the need for dynamic data-driven flight trajectory planning to advise pilots or control UAVs. While total loss of thrust trajectories to nearby…
Catching high-speed targets in the flight is a complex and typical highly dynamic task. In this paper, we propose Catch Planner, a planning-with-decision scheme for catching. For sequential decision making, we propose a policy search method…
Today, low-altitude fixed-wing Unmanned Aerial Vehicles (UAVs) are largely limited to primitively follow user-defined waypoints. To allow fully-autonomous remote missions in complex environments, real-time environment-aware navigation is…
Addressing airport traffic jams is one of the most crucial and challenging tasks in the remote sensing field, especially for the busiest airports. Several solutions have been employed to address this problem depending on the airplane…
With autonomous aerial vehicles enacting safety-critical missions, such as the Mars Science Laboratory Curiosity rover's landing on Mars, the tasks of automatically identifying and reasoning about potentially hazardous landing sites is…
The number of daily sUAS operations in uncontrolled low altitude airspace is expected to reach into the millions in a few years. Therefore, UAS density prediction has become an emerging and challenging problem. In this paper, a deep…
The environment of low-altitude urban airspace is complex and variable due to numerous obstacles, non-cooperative aircrafts, and birds. Unmanned aerial vehicles (UAVs) leveraging environmental information to achieve three-dimension…