Dynamical-Network Evaluation and Design Tools for Strategic-to-Tactical Air Traffic Flow Management

Abstract:

The objective of this research is to develop tools for comprehensive design and optimization of air traffic flow management capabilities at multiple spatial and temporal resolutions: at a national airspace-wide scale and one-day time horizon (strategic time-frame); and at a regional scale (of one or a few Centers) and a two-hour time horizon (tactical time-frame).Year 3 results are summarized in the following.

• WSU group has focused on two studies related to decision-making at the strategic scale. First, the effort to develop weather-impact models for strategic decision-making has been continued. Specifically, we have pursued the development of airport-impact models at the strategic horizon (2-15 hours). Specifically, a multinomial logistic regression model for airport arrival rates has been proposed, and has been developed in software and validated for multiple case-study airports (e.g., Boston's Logan airport). Second, we have proposed a methodology for the important task of selecting a small set of traffic-management-initiatives for design, on the day of operations. Specifically, we have put forth the perspective that highly simplified circuit-network models for traffic can permit crude evaluation of the ripple impact of weather, and in turn facilitate TMI selection. Core network-controls research is also being pursued in support of these objectives.
• Built upon the modeling and performance evaluation effort in Years 1 and 2, the focus of the UNT group in Year 3 has been on optimal management strategy design in the presence of both weather uncertainties. The specific outcomes include: 1) theoretic development of the multivariate probabilistic collocation method (PCM) for uncertainty evaluation and optimal management design (submitted to IEEE Trans. SMC), 2) application of the PCM method for designing optimal strategic management strategies, including routing, minute-in-trail (MIT), and ground delay programs (GDP) (published in AIAA Aviation), and 3) development of the jump-linear analytical approach for optimal routing management. The construction of a hierarchical center-sector stochastic transmission model as a framework for the strategic-to- tactical Traffic Flow Management scheme.
• At Purdue, the complete hierarchical center-sector stochastic transmission model is built and validated based on the Linear Dynamics System Model (LDSM) and the nationwide Aircraft Situation Display to Industry (ASDI) tracking data. The 20-center flow transmission network and its sub-networks are constructed. The time-variant transmission flow rates in the stochastic matrices for networks at both levels are calculated with air traffic tracking data. The hierarchical center-sector stochastic transmission model is used to simulate the uncontrolled and optimized traffic flow patterns in 20 centers and the sectors inside each center.

We envision that these results address critical needs in the strategic-to-tactical traffic management in the national airspace system (NAS). Moreover, the analytical tools developed broadly permit the tight conjoining of cyber- and physical- resources in designing decision-support capabilities for infrastructure networks.