Characterization of Days Based On Analysis of National Airspace System Performance Metrics
Characterization of Days Based On Analysis of National Airspace System Performance Metrics
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基于国家空域系统性能指标分析的天数特征
DOI：
10.2514/6.2007-6449
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发表时间：
2007
影响因子：
6
通讯作者：
Bassam Musaffar
中科院分区：
文献类型：
--
作者：
G. Chatterji;Bassam Musaffar
国家空域系统的运行天数可以根据交通需求、跑道状况、设备故障以及地面和航线天气状况来描述。这些原因体现在起飞延误、到达延误、途中延误和交通流量管理延误等方面。交通流量管理措施，如地面停止、地面延误计划、里程限制、改道和空中等待，是为了平衡空中交通需求和可用容量，以保持国家空域系统的运行效率。美国联邦航空管理局（FAA）在空中交通运营网络（OPSNET）和航空系统性能指标（ASPM）数据库中维护延误和其他统计数据。OPSNET数据包括仪表飞行规则（IFR）航班报告的15分钟以上的延误。受起飞延误、途中延误、到达延误和交通流量延误影响的飞机数量记录在OPSNET数据中。ASPM数据包括实际起飞次数、取消起飞次数、起飞正点百分比、登机口到达正点百分比、滑行延误。出租车延误，登机口延误，到达延误和阻塞延误。美国主要机场的地面状况根据仪器气象条件（IMC）和视觉气象条件（VMC）进行分类，作为ASPM数据中一天中时间的函数。本文的主要目标是使用OPSNET和ASPM数据将数据集中的日期分类为几个不同的组，其中每个组根据距离度量与其他组分开。对天进行分类的动机有两个方面：1)能够选择具有特定操作特征的交通天，使用全系统模拟系统（如美国国家航空航天局的空域概念评估工具（ACES））进行概念评估；2)能够根据分类组的特征对给定的一天进行评估。论文的第一部分致力于分析OPSNET和ASPM数据中的主要趋势。论文的第二部分描述了从OPSNET和ASPM数据中导出的适合表征日的特征或度量，以及用于对日进行分组的分类算法。最后，描述了根据群的性质来评价某一天的特征的方法。
Days of operations in the National Airspace System can be described in term of traffic demand, runway conditions, equipment outages, and surface and enroute weather conditions. These causes manifest themselves in terms of departure delays, arrival delays, enroute delays and traffic flow management delays, Traffic flow management initiatives such as, ground stops, ground delay programs, miles-in-trail restrictions, rerouting and airborne holding are imposed to balance the air traffic demand with respect to the available capacity, In order to maintain operational efficiency of the National Airspace System, the Federal Aviation Administration (FAA) maintains delay sad other statistics in the Air Traffic Operations Network (OPSNET) and the Aviation System Performance Metrics (ASPM) databases. OPSNET data includes reportable delays of fifteen minutes ox more experienced by Instrument Flight Rule (IFR) flights. Numbers of aircraft affected by departure delays, enroute delays, arrival delays and traffic flow delays are recorded in the OPSNET data. ASPM data consist of number of actual departures, number of canceled departures, percentage of on time departures, percentage of on time gate arrivals, taxi-out delays. taxi-in delays, gate delays, arrival delays and block delays. Surface conditions at the major U.S. airports are classified in terms of Instrument Meteorological Condition (IMC) and Visual Meteorological Condition (VMC) as a function of the time of the day in the ASPM data. The main objective of this paper is to use OPSNET and ASPM data to classify the days in the datasets into few distinct groups, where each group is separated from the other groups in terms of a distance metric. The motivations for classifying the days are two-fold, 1) to enable selection of days of traffic with particular operational characteristics for concept evaluation using system-wide simulation systems such as the National Aeronautics and Space Administration's Airspace Concepts Evaluation Tool (ACES) and 2) to enable evaluation of a given day with respect to the characteristics of the classified groups. The first part of the paper is devoted to the analysis of major trends seen in the OPSNET and ASPM data. The second part of the paper is devoted to describing features or measures derived from the OPSNET and ASPM data that are suitable for characterizing days, and the classification algorithm used for grouping the days. Finally, the method for evaluating the characteristics of a given day with respect to the properties of the groups is described.