滑行道路线支持系统的需求与决策模型

Dhara Modi, A. Fabregas, L. D. Otero
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引用次数: 4

摘要

机场是全球运输网络的主要组成部分,是不断改进运营的主题。商业航空工业在过去的几十年里经历了巨大的增长。这种蓬勃发展的需求产生了经济效益,然而,它也增加了机场的拥堵程度。虽然需求是经常性交通堵塞的一个原因,但其他形式的非经常性交通堵塞也很常见。极端天气事件、设备故障和安全威胁是导致非经常性拥塞的常见原因。本文介绍了系统工程过程在地面交通管制决策支持系统中的应用。所提出的模型应该能够帮助地面交通管制操作员以系统最优的方式在滑行道上安排飞机。展示了业务用例、需求、模型验证。建议的模型能够在操作层面处理经常性和非经常性拥塞。本文以中等至严重拥堵的单跑道机场为例,对所提出的模型进行了测试。有效减少的拥堵率从10%到14%不等,具体取决于滑行道的几何形状。研究结果令人鼓舞,表明所提出的模型是一个可行的概念,并且可以通过进一步的研究和开发来开发一个实用的系统。此外,管理层的非功能需求允许使用模型来确定容量,并度量操作性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Requirements and decision model for a taxiway route support system
Airports, are major components of the global transportation network and are the subject of continuous operational improvements. Commercial aviation industry has experienced substantial growth in the last decades. This booming demand generates economic benefits, however, it also increases the congestion levels at airports. While demand is a source of recurrent congestion, it is very common experience other forms of non-recurrent congestion. Extreme weather events, equipment failure and security threats are commonly encountered sources of non-recurrent congestion. This work presents the application of the systems engineering process to build a decision support system for ground traffic control. The proposed model should be able to assist ground traffic control operators to route planes in the taxiways in a system-optimal fashion. Business use cases, requirements, model verification, are presented. The proposed model is able to handle both, recurrent and non-recurrent congestion at the operational level. The proposed model is tested for a single runway airport case with moderate to heavy degree of congestion. Percentage of congestion effectively reduced ranged from 10% to 14%, depending on taxiway geometry. Results are encouraging enough to establish the proposed model as a feasible concept and, a practical system can be developed with further research and development. In addition, non-functional requirements at the management level allow using the model to determine capacity, and measure operational performance.
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