Coordination of operations with spatially and temporally shared resources, such as route segments, fixes, and runways, improves the efficiency of terminal airspace management. Problems in this category are, in general, computationally difficult compared to conventional scheduling problems. This paper presents a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA). It was first applied to a test problem introduced in existing literature. An experiment with a test problem showed that new methods can solve the 20 aircraft problem in fast time with a 65% or 440 second delay reduction using shared departure fixes. In order to test its application in a more realistic and complicated problem, the NSGA algorithm was applied to a problem in Los Angeles (LAX) terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial separation in current operations, which may introduce unnecessary delays. In this work, three types of separations-spatial, temporal, and hybrid separations-were formulated using the new algorithm. The hybrid separation combines both temporal and spatial separations. Results showed that although temporal separation achieved less delay than spatial separation with a small uncertainty buffer, spatial separation outperformed temporal separation when the uncertainty buffer was increased. Hybrid separation introduced much less delay than both spatial and temporal approaches. For a total of

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Cooperative control of multiple unmanned aerial vehicles (UAVs) poses significant theoretical and technical challenges. Recent advances in sensing, communication and computation enable the conduct of cooperative multiple-UAV missions deemed impossible in the recent past. We are interested in solving the Formation Reconfiguration Planning (FRP) problem which is focused on determining a nominal state and input trajectory for each vehicle such that the group can start from the given initial configuration and reach its given final configuration at the specified time while satisfying a set of given iiiter-and intra-vehicle constraints. Each solution of a FRP problem represents a distinct reconfiguration mode. When coupled with formation 'keeping modes, they can form a hybrid automaton of formation maneuvers in which a transition from one formation maneuver to another formation maneuver is governed by a finite automaton. This paper focuses on the implementation of the optimized hybrid system approach to formation reconfiguration for a group of 1 real and 3 virtual UAVs. Experimental results performed in the Richmond Field Station by using a helicopter-based Berkeley Aerial Robot are presented.

In terminal airspace, integrating arrivals and departures with shared waypoints provides the potential of improving operational efficiency by allowing direct routes when possible. Incorporating stochastic evaluation as a post-analysis process of deterministic optimization is one way to learn the impact of uncertainty and to avoid unexpected outcomes. This work presents a way to take uncertainty into consideration during the optimization. The impact of uncertainty was incorporated into cost evaluations when searching for the optimal solutions. The controller intervention count was computed using a heuristic model and served as another cost besides total delay. Costs under uncertainty were evaluated using Monte Carlo simulations. The Pareto fronts that contain a set of solutions were identified and the trade-off between delays and controller intervention count was shown. Solutions that shared similar delays but had different intervention counts were investigated. The results showed that optimization under uncertainty can identify compromise solutions and help decision-makers reduce controller intervention while achieving low delays.

This paper compares airspace design solutions for dynamically reconfiguring airspace in response to nominal daily traffic volume fluctuation. Airspace designs from seven algorithmic methods and a representation of current day operations in Kansas City Center were simulated with two times today's demand traffic. A three-configuration scenario was used to represent current day operations. Algorithms used projected unimpeded flight tracks to design initial 24-hour plans to switch between three configurations at predetermined reconfiguration times. At each reconfiguration time, algorithms used updated projected flight tracks to update the subsequent planned configurations. Compared to the baseline, most airspace design methods reduced delay and increased reconfiguration complexity, with similar traffic pattern complexity results. Design updates enabled several methods to as much as half the delay from their original designs. Freeform design methods reduced delay and increased reconfiguration complexity the most.