PI Name: Cynthia Barnhart Institution: Massachusetts Institute of Technology Proposal Number: 0735905
EFRI-ARESCI: Theory and Algorithms for Autonomous Reconfigurability of the National Air Transportation System
In this project, investigators from the Massachusetts Institute of Technology and the University of Texas-Austin address critical needs in the national air transportation system (NATS). Recent studies suggest that the current NATS is on the verge of becoming unstable, with disturbance-induced congestion and delays likely to arrest growth and expansion, rendering the existing system unsustainable. This research establishes the foundation for the comprehensive and fundamental restructuring of the NATS, towards an autonomously reconfigurable system capable of adapting rapidly to unforeseen events and disturbances, ranging from daily weather uncertainty (considered here), to emergencies and disaster response (an important topic of future research). This is accomplished through dynamic, distributed, iterative and optimization-based capacity allocation and scheduling mechanisms, complemented by dynamic pricing and collaborative arrangements between airlines. A three-stage iteration linking the FAA and the airlines is pursued: (1) capacity allocation: dynamic, spatial and temporal reconfiguration of capacity; (2) dynamic, spatial and temporal reconfiguration of demand; (3) dynamic pricing and collaborative arrangements between airlines. This iteration is supported by research addressing the theoretical and algorithmic foundations, analysis and synthesis, and reconfigurable system test beds through a sequence of five research thrusts: (i) dynamic reconfiguration of critical physical elements of the NATS; (ii) algorithms and models for air traffic flow management, and airline scheduling and recovery, under irregular operations; (iii) a new theory of dynamic and adaptable robustness in large-scale distributed optimization-based ATFM and airline models; (iv) market-based pricing mechanisms; (v) a model-based system test bed.
This project includes several education-based outreach initiatives. The Ph.D. students this funding supports will emerge with core competency in their field, supplemented by a much broader integrated base of knowledge, and with concrete experience working on a large-scale engineered system. An additional outcome will be joint curriculum development by the investigators, who will integrate material ranging from conceptual theoretical ideas to case studies in their graduate classes. The proposed research also provides an ideal opportunity for involving undergraduates in front-line research. Both MIT and UT Austin are committed to such initiatives, with particular emphasis on involving women and minorities.
