EFRI-ARESCI: Theory and Algorithms for Autonomous Reconfigurability of the National Air Transportation System

项目名称：Cynthia barnhart机构：麻省理工学院提案号：0735905EFRI-ARESCI：国家航空运输系统自主可重构性的理论和算法在这个项目中，来自麻省理工学院和德克萨斯大学奥斯汀分校的研究人员解决了国家航空运输系统（NATS）的关键需求。最近的研究表明，目前的NATS正处于变得不稳定的边缘，干扰引起的拥堵和延误可能会阻止增长和扩张，使现有系统不可持续。本研究为NATS的全面和根本性重组奠定了基础，朝着能够快速适应不可预见事件和干扰的自主可重构系统发展，范围从日常天气的不确定性（这里考虑）到紧急情况和灾害响应（未来研究的一个重要主题）。这是通过动态、分布式、迭代和基于优化的运力分配和调度机制来实现的，并辅以航空公司之间的动态定价和协作安排。将FAA和航空公司联系起来的三个阶段迭代是：(1)容量分配：容量的动态、空间和时间重构；(2)需求的动态、时空重构；(3)航空公司之间的动态定价和合作安排。通过五个研究重点，研究理论和算法基础、分析和综合以及可重构系统测试平台，支持这一迭代：(i) NATS关键物理元素的动态重新配置；（ii）在不正常运作情况下的空中交通流量管理、航班调度和恢复的算法和模型；(3)基于大规模分布式优化的ATFM和航线模型的动态和自适应鲁棒性新理论；市场定价机制；(v)基于模型的系统试验台。该项目包括若干以教育为基础的外联倡议。该基金支持的博士生将在他们的领域中具有核心竞争力，辅以更广泛的综合知识基础，以及在大型工程系统中工作的具体经验。另一项成果将是由研究人员共同开发课程，他们将在研究生课程中整合从概念理论思想到案例研究的各种材料。建议的研究也为本科生参与一线研究提供了一个理想的机会。麻省理工学院和德克萨斯大学奥斯汀分校都致力于这样的举措，特别强调让女性和少数族裔参与进来。

PI Name: Cynthia BarnhartInstitution: Massachusetts Institute of TechnologyProposal Number: 0735905EFRI-ARESCI: Theory and Algorithms for Autonomous Reconfigurability of the National Air Transportation SystemIn 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.