Monitoring and evaluating failure-sensitive strategies in air traffic control simulator training

Stathis Malakis, T. Kontogiannis, Panos Psaros
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引用次数: 2

Abstract

The introduction of new air traffic management systems changes the demands on the provision of Air Traffic Control (ATC) services. At the core of the system air traffic controllers are responsible for the safe, expeditious and orderly flow of the air traffic. The growth of air traffic requires an increase in the capacity of the airspace, controller tools, and operating procedures. In the case of modern ATC operations, we are dealing with a complex; information rich and dynamic environments that require air traffic controllers to attend to multiple events anticipate aircraft conflicts, implement new concepts and make sense of evolving scenarios. Major system wide interventions; the Single European Sky Air Traffic Management Research (SESAR) and Next Generation Air Transportation System (NextGen) present significant changes to the delegation of authority between pilots and controllers, which requires further research on how controllers employ failure sensitive strategies in complex scenarios. Failure sensitive strategies in the context of Cognitive Systems Engineering refer to higher level strategies related to macrocognitive processes (e.g., problem solving), which are supported by the same automation functions as normal operations. High-level strategies are essential in keeping the system safe, and include strategies that forestall possibilities for failure. Normal day-today operations require conflict resolution strategies and abnormal situations call for high-level strategies. Studying how controllers employ failure sensitive strategies to cope with traffic complexity is very important if we are to understand how modern information technology and new operational demands may affect system performance. To this end, an observational field study was performed during the annual refresher training of Air Traffic Controllers in a medium complexity European airport with seasonal traffic. This was later complemented with a follow up small scale trail on simulator training to corroborate initial findings. The purpose of the study was to explore the capabilities of existing simulator based training in monitoring and evaluating failure-sensitive strategies in normal operations where new concepts are employed. Initial results indicated that current simulators can be a useful tool in monitoring and evaluating failure sensitive strategies without substantial alterations of their characteristics and in line with training curricula. In a first level and using cognitive task analysis failure sensitive strategies were elicited and documented. In a second level, a set of user centred requirements was compiled towards the development of a low cost debriefing tool based on existing simulators and training practices. In a third and final level a complexity metrics was developed in order to define thresholds of cognitive complexity that prevent controllers from full implementation of new concepts on day to day operations. Practical benefits can be derived especially in the areas of decision support systems, safety management systems (e.g. supporting safety assessments of new concepts) and training in the context of SESAR and NextGen.
空中交通管制模拟器训练中故障敏感策略的监测与评估
新的航空交通管理系统的引入,改变了航空交通管制服务的需求。在这个系统的核心,空中交通管制员负责安全、快速和有序的空中交通。空中交通的增长要求空域容量、管制工具和操作程序的增加。在现代空中交通管制的情况下,我们正在处理一个复杂的;信息丰富和动态的环境要求空中交通管制员参与多个事件,预测飞机冲突,实施新概念并理解不断发展的场景。主要的全系统干预措施;单一欧洲天空空中交通管理研究(SESAR)和下一代航空运输系统(NextGen)对飞行员和管制员之间的授权进行了重大改变,这需要进一步研究管制员如何在复杂情况下采用故障敏感策略。认知系统工程背景下的故障敏感策略是指与宏观认知过程(如解决问题)相关的更高层次的策略,这些策略由与正常操作相同的自动化功能支持。高级策略在保持系统安全方面是必不可少的,并且包括预防失败可能性的策略。正常的日常操作需要冲突解决策略,而异常情况则需要高级策略。如果我们要了解现代信息技术和新的操作需求如何影响系统性能,研究控制器如何采用故障敏感策略来应对流量复杂性是非常重要的。为此目的,在一个具有季节性交通的中等复杂性欧洲机场的空中交通管制员年度进修培训期间进行了实地观察研究。后来又对模拟器训练进行了小规模的跟踪,以证实最初的发现。这项研究的目的是探索现有的基于模拟器的训练在监测和评估在使用新概念的正常操作中故障敏感战略方面的能力。初步结果表明,目前的模拟器可以成为监测和评价对失败敏感的战略的有用工具,而无需对其特性进行重大改变并符合培训课程。在第一层次,运用认知任务分析,引出并记录了失败敏感策略。在第二级,编制了一套以用户为中心的要求,以便根据现有模拟器和培训做法开发一种低成本的情况汇报工具。在第三个也是最后一个层面,我们开发了一个复杂性指标,目的是定义认知复杂性的阈值,防止控制者在日常操作中完全执行新概念。特别是在决策支持系统、安全管理系统(例如支持新概念的安全评估)以及SESAR和NextGen背景下的培训方面,可以获得实际效益。
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