Improving runway queue management: Modifying SDSS to accommodate deicing

B. Wilson, P. Hurley, P. Diffenderfer
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引用次数: 3

Abstract

The FAA is sponsoring research in NextGen Surface-Trajectory-Based Operations (STBO). Surface tactical flow is a component of STBO. Collaborative Departure Queue Management (CDQM), a decision support tool (DST) used to support surface tactical flow, is currently being demonstrated at two airports, neither of which experience frequent snow events. The CDQM DST is hosted on a prototype Surface Decision Support System (SDSS), which models surface traffic and predicts runway queues. To function during snow events, SDSS will need to account for different taxi routes and additional time that deicing requires. Simply put, SDSS will need to know where deicing takes place and how long it will take. To better understand deicing, an interview team, the authors of this paper, visited four northern airports. Prior to the visits the interview team enumerated a series of topics and questions for each topic. The team also identified entities (flight operators, Air Traffic Control (ATC), and the local airport authority) it wished to interview at each airport, as well as personnel in specific positions within each of these entities. Each airport visit spanned two days. From the visits, we learned where and how flight operators deice aircraft and how airport authorities manage runway closures during snow events. Two of the airports, Detroit Metro Airport (DTW) and Minneapolis-St. Paul International Airport (MSP), perform the majority of their deicing at centralized deicing pads in the movement area. At Boston Logan International Airport (BOS), most of the deicing occurs in the ramp area. At Chicago O'Hare International Airport (ORD) all of the deicing occurs in the ramp area. As for modifying the SDSS to accommodate deicing, three options are available. One, insert deicing times into the SDSS “back-calculation” sequence, allowing extra time for deicing-time uncertainty. Two, attempt to model deicing times, providing SDSS with improved estimates. Three, begin the SDSS back calculation after deicing. Research in these areas will continue.
改善跑道队列管理:修改SDSS以适应除冰
美国联邦航空局正在资助下一代基于表面轨迹的作战(STBO)的研究。地面战术流是STBO的一个组成部分。协同离境队列管理(CDQM)是一种决策支持工具(DST),用于支持地面战术流程,目前正在两个机场进行演示,这两个机场都没有经历过频繁的降雪事件。CDQM DST基于地面决策支持系统(SDSS)原型,该系统模拟地面交通并预测跑道队列。为了在雪天期间发挥作用,SDSS需要考虑到不同的出租车路线和除冰所需的额外时间。简单地说,SDSS需要知道除冰发生在哪里以及需要多长时间。为了更好地了解除冰,本文的作者,一个采访小组,访问了四个北方机场。在访问之前,访谈团队为每个主题列举了一系列主题和问题。视察队还确定了它希望在每个机场会见的实体(飞行经营者、空中交通管制和当地机场当局),以及在每个这些实体内担任特定职位的人员。每次机场访问持续两天。通过参观,我们了解到航班运营商在哪里以及如何配置飞机,以及机场当局如何管理雪天期间跑道关闭的情况。其中两个机场,底特律地铁机场(DTW)和明尼阿波利斯-圣。保罗国际机场(MSP)的大部分除冰工作都是在机区的集中除冰垫进行的。在波士顿洛根国际机场(BOS),大部分除冰发生在坡道区域。在芝加哥奥黑尔国际机场(ORD),所有的除冰都发生在坡道区域。至于修改SDSS以适应除冰,有三种选择。首先,将除冰时间插入SDSS“反向计算”序列,为除冰时间的不确定性留出额外的时间。第二,尝试建立除冰时间模型,为SDSS提供更好的估计。三、除冰后开始SDSS反算。这些领域的研究将继续进行。
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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