A User-Driven Prioritisation Process implementation and optimisation for ATFM hotspot resolution

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY Transportation Research Part C-Emerging Technologies Pub Date : 2024-11-06 DOI:10.1016/j.trc.2024.104894
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Abstract

The current and forecast air traffic levels lead to demand-capacity imbalances, which are dealt with by delaying flights through the allocation of air traffic flow management (ATFM) slots. To mitigate the delay impact on airspace users (AUs) and passengers, User Driven Prioritisation Process (UDPP) solutions are under development, with the goal to enhance flexibility for airlines to prioritise their own flights in the ATFM regulations. UDPP solutions are developed in collaboration with AUs, achieving high maturity level and even operational use at some airports.
While UDPP solutions in reality are still based on manual or semi-automated procedures, in this paper we show that when an airline has an accurate delay cost model at disposal, the prioritisation process can be fully automated via an integer programming model that provides the prioritisation that optimises the AUs’ UDPP exploitation. We use this automated process and the implementation of the UDPP mechanism to provide an estimation of the benefits of UDPP in terms of cost with respect to the current ATFM regulation process.
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为解决 ATFM 热点问题而实施和优化用户驱动的优先排序程序
当前和预测的空中交通流量水平导致需求与容量失衡,通过分配空中交通流量管理(ATFM)时段来解决航班延误问题。为减轻延误对空域用户(AUs)和乘客的影响,目前正在开发用户驱动优先程序(UDPP)解决方案,目的是提高航空公司在 ATFM 规定中优先安排自己航班的灵活性。虽然 UDPP 解决方案在现实中仍以手动或半自动程序为基础,但在本文中,我们展示了当航空公司拥有准确的延误成本模型时,可通过整数编程模型实现优先级排序过程的完全自动化,从而优化非盟的 UDPP 利用。我们利用这一自动化流程和 UDPP 机制的实施,估算了 UDPP 在成本方面相对于当前 ATFM 监管流程的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
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