A hierarchical framework for air traffic control.

摘要

Air travel in recent years has been plagued by record delays, with over ;A hierarchical framework is developed to simultaneously solve the sometimes conflicting goals of regional efficiency and local safety. Careful attention is given in defining the interactions between the layers of this hierarchy. In this way, solutions to individual air traffic problems can be targeted and implemented as needed. First, the regional traffic flow management problem is posed as an optimization problem and shown to be NP-Hard. Approximation methods based on aggregate flow models are developed to enable real-time implementation of algorithms that reduce the impact of congestion and adverse weather. Second, the local trajectory design problem is solved using a novel slot-based sector model. This model is used to analyze sector capacity under varying traffic patterns, providing a more comprehensive understanding of how increased automation in NextGen will affect the overall performance of air traffic control.;The dissertation also provides solutions to several key estimation problems that support corresponding control tasks. Throughout the development of these estimation algorithms, aircraft motion is modeled using hybrid systems, which encapsulate both the discrete flight mode of an aircraft and the evolution of continuous states such as position and velocity. The target-tracking problem is posed as one of hybrid state estimation, and two new algorithms are developed to exploit structure specific to aircraft motion, especially near airports. First, discrete mode evolution is modeled using state-dependent transitions, in which the likelihood of changing flight modes is dependent on aircraft state. Second, an estimator is designed for systems with limited mode changes, including arrival aircraft. Improved target tracking facilitates increased safety in collision avoidance and trajectory design problems. A multiple-target tracking and identity management algorithm is developed to improve situational awareness for controllers about multiple maneuvering targets in a congested region. Finally, tracking algorithms are extended to predict aircraft landing times; estimated time of arrival prediction is one example of important decision support information for air traffic control.