Systemic identification of airspace collision risk tipping points using an evolutionary multi-objective scenario-based methodology

One key measure for judging on the safety of operations in an airspace is the collision risk estimate. Comparing this estimate to the target level of safety (TLS), a quantitative value provides an objective assessment on airspace safety of operations. However, this quantitative value does not provide any reasoning or insight on the interaction between sector and traffic features on the one hand, and the air traffic controllers (ATC) actions for traffic flow management (TFM) on the other hand. There are two fundamentally different approaches to manage high risk scenarios. One is post the event, where we need to ask what we should do to reduce risk in a scenario that is already high risk. The second is a preventive pre-the-event approach, where we can ask the question of what are the causes that make a low risk scenario becoming a high risk one. By identifying these causes, one can prevent risk to escalate. This paper is about this second approach. We propose an evolutionary multi-objective scenario-based methodology for the systemic identification of airspace collision risk tipping points. The methodology attempts to help us to gain insight into the interaction of traffic and sector features with ATC actions that can lead to an increase in collision risk in an otherwise low risk traffic scenario. Results indicate that "risk-free" scenarios having collision risk below the TLS can become "risk-prone" by very few or even just one ATC action. We found that a "Turn To Next Waypoint" ATC action, which is very common in traffic flow management for expediting aircraft to meet their metering requirements, may significantly increase collision risk due to unexpected flight crossings with undesired crossing angles and relative speed with other aircraft in the vicinity. The results also provide an understanding of ATC actions in a given scenario that should be avoided to reduce collision risk. (C) 2013 Elsevier Ltd. All rights reserved.