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We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.

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This paper is concerned with the optimization of lateral-escape trajectories in a microburst wind field for an aircraft on final approach. The objective is to minimize the peak value of altitude drop. An extensive numerical effort has been undertaken to investigate the characteristics of open-loop extremal solutions for various locations of the microburst. When a sufficiently large aerodynamic roll-angle limit is specified and the center of the microburst is not too far offset from the centerline extension of the approach runway, typically three trajectories can be found that satisfy the first-order necessary conditions of optimality for a given set of boundary conditions, namely, a trajectory that passes the microburst center to the left, a trajectory passing the center to the right, and a trajectory passing right through the center. The results bear out that a lateral-escape maneuver, in which an aircraft is turned away from the microburst center, may significantly improve an aircraft's surv ivability, in comparison to an escape maneuver that is restricted to a vertical plane. One of the most striking observations in this study is that, in contrast to nonturning escape maneuvers, lateral-escape maneuvers often exhibit a climb, rather than a descent, in the initial phase. The insight obtained from the present study may help the development of near-optimal lateral-escape guidance strategies for onboard application.

Abstract:In an effort to allow to increase the number of aircraft and airport operations while mitigating their negative impacts (e.g., noise and pollutant emission) on near-airport communities, the optimal design of new departure routes with less noise and fuel consumption becomes more important. In this paper, a multi-objective evolutionary algorithm based on decomposition (MOEA/D), which recently emerged as a potential method for solving multi-objective optimization problems (MOPs), is developed for this kind of problem. First, to minimize aircraft noise for departure routes while taking into account the interests of various stakeholders, bi-objective optimization problems involving noise and fuel consumption are formulated where both the ground track and vertical profile of a departure route are optimized simultaneously. Second, in order to make the design space of vertical profiles feasible during the optimization process, a trajectory parameterization technique recently proposed is employed. Furthermore, some modifications to MOEA/D that are aimed at significantly reducing the computational cost are also introduced. Two different examples of departure routes at Schiphol Airport in the Netherlands are shown to demonstrate the applicability and reliability of the proposed method. The simulation results reveal that the proposed method is an effective and efficient approach for solving this kind of problem.