CAREER: Practical Algorithms for Next Generation Air Transportation Systems

本提案的核心观点是，通过分析大量的天气和航空公司数据，我们可以(1)使用天气预报来确定对不确定性具有鲁棒性的航班时刻表，(2)设计基于市场的机制来管理航空公司对稀缺资源的竞争，以及(3)将环境因素纳入我们的优化框架。智力优势：该提案同时解决了三个挑战：健壮性、竞争实体和环境问题。这样做将改善现状，导致新的优化算法和基于市场的机制，可以处理不断增加的空中交通负荷。了解天气现象及其对行动的影响，将有助于更好地对空中交通进行战略和战术控制。公平的资源分配算法将鼓励航空公司如实报告运营数据，为信息共享提供激励，并改善乘客体验。绿色空中交通管理算法将在可容忍的环境影响下支持增加的空中交通负荷。更广泛的影响：本研究的结果将通过适应监管约束，提供一个更有效、更稳健和更安全的航空运输系统，并制定航空运输政策。与麻省理工学院林肯实验室和美国宇航局艾姆斯研究中心的合作将通过为空中交通管制员开发决策支持工具，使这项研究的结果得以实施。教育计划包括开发一门新的麻省理工学院课程，内容是应用于基础设施系统的优化和控制技术。该计划还包括开发交互式网络材料，向公众揭开空中交通管制的神秘面纱，并教育K-12学生了解一项重要的工程挑战。

CAREER: PRACTICAL ALGORITHMS FOR NEXT GENERATION AIR TRANSPORTATION SYSTEMSThe core insight in this proposal is that by analyzing the large amounts of weather and airline data, we can (1) use weather forecasts to determine schedules that are robust to uncertainty, (2) design market-based mechanisms that manage airline competition for scarce resources, and (3) incorporate environmental considerations into our optimization framework.Intellectual merit:This proposal simultaneously addresses three challenges: robustness, competing entities and environmental concerns. Doing so will improve on the status quo, leading to novel optimization algorithms and market-based mechanisms that can handle increasing air traffic loads. Understanding weather phenomena and their effect on operations will allow better strategic and tactical control of air traffic. Equitable resource allocation algorithms will encourage truthful reporting of operational data by the airlines, provide incentives for information sharing, and improve passenger experience. Green air traffic management algorithms will support increased air traffic loads with a tolerable environmental impact. Broader impact: The results of this research will offer a more efficient, robust and safe air transportation system by accommodating regulatory constraints, and shape air transportation policy. Collaborations with MIT Lincoln Laboratory and NASA Ames Research Center will enable the implementation of the results of this research through the development of decision support tools for air traffic controllers. The education plan includes the development of a new MIT course on optimization and control techniques applied to infrastructure systems. The plan also includes the development of interactive web-based materials to demystify air traffic control to the general public, and to educate K-12 students on an important engineering challenge.