The objective of the research is to develop tools for comprehensive design and optimization of air traffic flow management capabilities at multiple spatial and temporal resolutions: 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). The approach is to develop a suite of tools for designing complex multi-scale dynamical networks, and in turn to use these tools to comprehensively address the strategic-to-tactical traffic flow management problem.
The two directions in tool development include 1) the meshed modeling/design of flow- and queueing-networks under network topology variation for cyber- and physical- resource allocation, and 2) large-scale network simulation and numerical analysis. This research will yield aggregate modeling, management design, and validation tools for multi-scale dynamical infrastructure networks, and comprehensive solutions for national-wide strategic-to-tactical traffic flow management using these tools.
The broader impact of the research lies in the significant improvement in cost and equity that may be achieved by the National Airspace System customers, and in the introduction of systematic tools for infrastructure-network design that will have impact not only in transportation but in fields such as electric power network control and health-infrastructure design. The development of an Infrastructure Network Ideas Cluster will enhance inter-disciplinary collaboration on the project topics and discussion of their potential societal impact. Activities of the cluster include cross-university undergraduate research training, seminars on technological and societal-impact aspects of the project, and new course development.
The objective of the research is to develop tools for comprehensive design and optimization of air traffic flow management capabilities at multiple spatial and temporal resolutions: 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). The strategic time-frame, typically 2-15 hours in advance, is critical for National Airspace System (NAS) resource planning to resolve the inconsistencies between traffic demands and limited airspace capacities. While significant advances have been made to tactical air traffic management, research to automate air traffic management at the strategic timeframe has been very limited. The University of North Texas team led the development of the foundational framework and models for strategic air traffic management, which also facilitates smooth transitioning of strategic decisions to the tactical management. Our research tackles the key challenge in strategizing air traffic flow management---uncertain weather impact. We have developed models, simulators, analytical methods, and tools that resolve the challenge. Intellectual Merits: In particular, key intellectual merits include the following. The first is the dynamic NAS model that permits real-time strategic management. The advanced queuing network-based NAS model reveals the most intrinsic impact of management actions on traffic flows, and addresses both the large scale and the stochastic nature of the NAS. The second is the NAS simulator that simulates and evaluates traffic dynamics in the NAS under weather and demand uncertainties. The third is the modeling framework that integrates three pieces (demand model, weather model, and management) to serve as the foundational framework for tractable evaluation and design of management strategies. The fourth is the jump-linear approach for the evaluation of uncertain weather impact on the statistics of delayed traffic. The fifth is the M-PCM-OFFD approach to evaluate and design optimal management strategies under multidimensional uncertainties. The last but not the least is the spatiotemporal dynamic data driven clustering approach to facilitate contingency decision-making under uncertainty. Broad Impact: Our research results are documented in ~40 publications, and have made significant impact to the air traffic management community, as reflected by a large number of following works and a shifting focus toward automating strategic air traffic management and studying weather impact. The core models, simulators, analytical methods, and tools that we have developed not only apply to the air traffic field, but also to other large-scale infrastructure systems where decision-making under environmental uncertainties is involved. We have extended the results obtained from the grant to energy management and to complex information systems. The collaboration with MITRE has led to technology transfer and the inclusion of work into the FAA’s work packages. We expect that our research results will produce significant societal impact by improving the safety and efficiency of the NAS, and by identifying common underlying challenges in managing large-scale infrastructures under weather uncertainty. The PI also actively pursued broad dissemination through presenting invited talks at universities, industry, government industries, and public events. In addition, the PI also participated in drafting the research roadmap on aviation for multiple professional communities. Educational activities include the development of a "Systems Modeling and Simulation" course which has attracted students from all five engineering departments, involving two undergraduate students, 6 Master students and 2 Ph.D. students in research, outreach to local high school through a Summer Teacher Research Program, and guiding the IEEE Robotics and Automation Student Chapter at the University of North Texas.
