Integrating Safety Metrics into the Arrival Capacity Management of large Aerodromes

通过在各个项目中主持制定的机场附近社会技术系统“空中交通管制”的安全分析方法，目前复杂机场的与能力有关的进场管制现在应纳入一个全面的优化过程，特别注重空中交通安全。今天的控制程序是基于对路线设计、程序规则和边界条件的上游安全评估。然而，在业务使用中，系统受到重大波动(天气、交通组成)的影响，目前只记录了业务业绩指标，并根据本身证明了“括号前”的安全性。这一实际误差被接近飞机之间的间隔值的保守规则所抵消，但它不会导致系统达到整体最优运行状态。通过将安全评估整合为一个在线程序，它旨在达到一个战术级别，即安全分析不断包括在性能评估中，从而利用额外的空域和跑道容量。必须知道定量安全指标(碰撞/事故概率)与各种生态/经济性能特征(容量、环境、成本效率)之间的相关性，这是以前从未获得的事实。危险潜力和所谓的“交通复杂性”之间的正相关被假定为熵，即作为对运输系统中的无序性和工作量的度量，已经有了部分经过验证的模型。由于可以假设这两个目标函数之间存在矛盾，因此将进一步研究ATM在这方面的权衡关系：在方法论上，多目标优化方法将被应用于主席可用的基于代理的快速仿真。

By means of safety analysis methods for the socio-technical system "Air Traffic Control" in the vicinity of airports which were developed at the chair in various projects, today's capacity-relevant approach control of complex airports shall now be integrated into an overall optimization process with special focus on air traffic safety. Today's control procedures are based on an upstream safety assessment of route design, procedural rules and boundary conditions. In operational use, however, the system is bounced by significant fluctuations (weather, traffic composition), and only operational performance indicators are currently recorded and safety "in front of the parentheses" is certified as per se. This factual error is countered by conservative rules for separation values between approaching aircraft, but it does not lead the system to an overall optimal operating state. By integrating the safety assessment as an online procedure, it is intended to achieve a tactical level where safety analyses are constantly included in the performance assessment and thus leverage additional airspace and runway capacity.The correlation between quantitative safety indicators (collision/incidence probabilities) and the various ecological/economic performance characteristics (capacity, environment, cost efficiency) must be known, a previously unattained fact. A positive correlation between hazard potential and so-called "traffic complexity" is postulated as entropy, i.e. as a measure of disorder and thus of workload in the transport system, for which partially validated models are already available. Since it can be assumed that there is a contradiction between the two objective functions, the relationship between trade-offs in the ATM in this respect will be investigated further: Methodologically, multi-objective optimization methods are to be applied to an agent-based fast-time simulation available at the chair.