Advanced flight planning algorithms

先进的飞行规划算法

• 批准号: 530692-2018
• 负责人: Rokne, Jon
• 金额: $ 1.81万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=663609
• 关键词: Advanced; flight; planning; algorithms

Over the last few decades, air traffic demand has increased globally, and this trend is predicted to continue during the next years. New air traffic flow management solutions are being developed as described in global air navigation plan of the International Civil Aviation Organization (ICAO) (ICAO, 2013). For this purpose, different programs have started to enhance navigation solutions and standards. These programs converge in the evolution of air traffic management into an automated, integrated, and interoperable environment. Devising optimal trajectories considering air traffic, control constraints, weather and winds, local climb and descent requirements, airplane weights and payloads led NASA (Ames Research Center) to develop its first flight planning software in 1979. Since then, a host of flight planning products have being built by industry leaders. In this project, the aim is to use data-mining, machine learning and artificial intelligence techniques to develop a system that will optimize a database engine that will optimize, retrieve and process data from sql , nosql, and in memory platforms for given parameters defined for a flight (e.g., route, airways, departure and arrival procedures, , etc.). A second objective is to develop this capability as adaptive to incorporate a variety of external factors which may directly or indirectly affect a flight route. Such advanced system should be made available on a wide variety of platforms, including stationary computers, laptops, handheld devices, etc. The resulting technology delivered out of the project will be used as part of the Skyplan flight planning software. As a result, Skyplan will be able to significantly improve their effectiveness in serving their customers, which in turn will be able to select better candidate flight plans. The increased accuracy in matching flights to flight plans has the potential of improving safety of flights, decrease cost of flights and improve the flight experience for customers. Furthermore, the research performed under the ENGAGE project will enable Skyplan Services LTD., a unique Canadian company, to retain market share in a very competitive market and to possibly expand their client list.****************

在过去的几十年里，全球航空交通需求不断增加，预计这一趋势将在未来几年继续下去。 如国际民用航空组织（ICAO）全球空中导航计划（ICAO，2013年）所述，正在开发新的空中交通流量管理解决方案。 为此，不同的计划已经开始加强导航解决方案和标准。这些程序在空中交通管理向自动化、集成化和互操作环境的演变中融合。考虑到空中交通、控制约束、天气和风、当地爬升和下降要求、飞机重量和有效载荷，NASA（艾姆斯研究中心）在1979年开发了第一个飞行规划软件。 从那时起，许多飞行计划产品已经由行业领导者建立。在这个项目中，目标是使用数据挖掘，机器学习和人工智能技术来开发一个系统，该系统将优化数据库引擎，该引擎将优化，检索和处理来自sql，nosql和内存平台的数据，用于为飞行定义的给定参数（例如，路线、航空公司、出发和到达程序等）。第二个目标是发展这种能力，使其能够适应各种可能直接或间接影响飞行路线的外部因素。这种先进的系统应可用于各种平台，包括固定式计算机，笔记本电脑，手持设备等，由此产生的技术交付的项目将被用作Skyplan飞行规划软件的一部分。 因此，Skyplan将能够显著提高其服务客户的效率，从而能够选择更好的候选飞行计划。将航班与飞行计划相匹配的准确性的提高有可能提高飞行安全性，降低飞行成本并改善客户的飞行体验。此外，在ENGAGE项目下进行的研究将使Skyplan Services Ltd.，一家独特的加拿大公司，在竞争激烈的市场中保持市场份额，并可能扩大其客户名单。**