Trajectory optimisation has shown good potential to reduce environmental impact in aviation. However, a recurring problem is the loss in airspace capacity that fuel optimal procedures pose, usually overcome with speed, altitude or heading advisories that lead to more costly trajectories. This paper aims at the quantification in terms of fuel and time consumption of implementing suboptimal trajectories in a 4D trajectory context that use required times of arrival at specific navigation fixes. A case study is presented by simulating conflicting Airbus A320 departures from two major airports in Catalonia. It is shown how requiring an aircraft to arrive at a waypoint early or late leads to increased fuel burn. In addition, the efficiency of such methods to resolve air traffic conflicts is studied in terms of both fuel burn and resulting aircraft separations. Finally, various scenarios are studied reflecting various airline preferences with regards to cost and fuel burn, as well as different route and conflict geometries for a broader scope of study.

This paper proposes an optimisation framework that computes conflict free optimal trajectories in dense terminal airspace, while continuously monitoring trajectory conformance in an effort to improve predictability. The objective is to allow, as much as possible, continuous vertical trajectory profiles without impacting negatively on airspace capacity. Given ADS-B (Automatic Dependent Surveillance-Broadcast) intent information, we predict the future state of potential intruder aircraft and use this nominal trajectory as a constraint in the ownship trajectory optimisation process. In it, a continuous multiphase optimal control problem is solved, taking into account spatial and temporal constraints. Additionally, a linearised Kalman filter keeps track of the target by estimating the deviations of its actual trajectory from its nominal trajectory, issuing a warning when an appropriate threshold is exceeded. This may be due to unexpected events, biases in the performance and weather models, wrong parameter assumptions, etc. An illustrative example is given, based on a computer simulation of two hypothetical trajectories in the Barcelona terminal manoeuvring area. The results show how this framework resolves the problem of uncertainties in the trajectory predictions and results in a more efficient conflict resolution.

Air traffic predictability is paramount in the air traffic system in order to enable concepts such as Trajectory Based Operations (TBO) and higher automation levels for selfseparation. Whereas in simulated environments 4D conflictfree trajectory optimisation has shown good potential in the improvement of air traffic efficiency, its application to real operations has been very challenging due to the current lack of information sharing between airspace users. Consequently, such operations are still very limited in scope and rarely attempted in dense traffic situations. Better predictability of other traffic future states would be an enabler for each aircraft to fly its user preferred route without decreasing safety in a self-separation context. But this is not an easy task when basic aircraft parameters such as aircraft weight, performance data or airline strategies are not available at the time of prediction. In this paper the authors propose to compensate this hindrance by continuously integrating the state of the surounding traffic to improve the ownship's knowledge of other aircraft's dynamics. Specifically, conventional position (and velocity) messages, as coming from Automatic Dependent Surveillance Broadcast (ADS-B), are integrated at the ownship. Then, an optimisation problem is formulated, using optimal control theory, that minimises the error with the known states, having the parameters of study (i.e. mass) as decision variables. A scenario with two departing trajectories is used to demonstrate the effectiveness of this parameter estimation method. In it, the take-off mass of the potential intruder is estimated onboard the ownship and its impact to conflict detection and resolution is presented, demonstrating the big improvements in predictability and safety.

ABSTRACT:This paper discusses the development of navigation algorithms to enable seamless operation of a small-size multi-copter in an indoor-outdoor environment. In urban and indoor environments a GPS position capability may be unavailable not only due to shadowing, significant signal attenuation or multipath, but also due to intentional denial or deception. The proposed navigation algorithm uses data from a GPS receiver, multiple 2D laser scanners, and an Inertial Measurement Unit (IMU). This paper addresses the proposed multi-mode fusion algorithm and provides initial result using flight test data. This paper furthermore describes the 3DR hexacopter platform that has been used to collect data in an operational environment, starting in an open environment, transitioning to an indoor environment, traversing a building, and, finally, transitioning back to the outdoor environment. Implementation issues will be discussed.

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