Air Traffic Complexity Map based on Non Linear Dynamical Systems

Abstract

This work presents a new air traffic complexity metric based on non-linear dynamical systems. Previous work has shown that the structure and organization of traffic are important factors in the perception of the complexity of an air traffic situation. The new metric captures these important aspects of complexity by identifying the organization of trajectories in a traffic pattern. This paper investigates only the features of this new metric without quantifying directly the connection between complexity and the metric. Authors of previous work in this area have proposed metrics that generally have not explicitly addressed the effects of organization in the traffic flow on complexity. In order to capture the effect of organization, the metric is based on a dynamical system which fits as closely as possible the observations given by the aircraft positions and speeds. This approach, uses a non-linear dynamical system model that fits the observations without error. Based on this non linear dynamical system the method consist in the computation of the map of the associated Lyapunov exponents. This metric can be used to identify high (or low) complexity areas on a map, and, by capturing the organization properties of the traffic, captures some of the key factors involved in ATC complexity. Such maps are an example of the usefulness of these methods for comparing the relative complexity of different regions of airspace 1 .

Distributed traffic complexity management by preserving trajectory flexibility

“…Pilots are assisted in conflict detection and resolution by cockpit automation, such as the AOP system, thus maintaining their workload at an acceptable level [8]. The allocation of separation assurance tasks to pilots reduces traffic complexity from a centralized perspective, which represents controller workload and proneness to separation violation errors [15,16], because the controller is relieved from active separation assurance for selfseparating aircraft. In addition, a notion of distributed/automated traffic complexity is introduced representing proneness to separation violation errors in the new distributed/automated environment.…”

A Genetic Algorithm-based BP Neural Network Method for Operational Performance Assessment of ATC Sector

“…Furthermore, the complexity of air traffic flow is proposed for the recognition of air traffic situation in airspace, which is more accurate, comprehensive and dynamic than airspace capacity and its utilization. As the most representative assessment technique for the complexity of air traffic flow, dynamic density concept has been measured by detecting aircraft altitude, speed and heading changing times [32][33][34][35][36][37]. Even though ATCO workload is not directly related to operational performance of ATC sector, it is a kind of essential investment to implement ATC operation, and has great influence on the operational performance.…”

Analysis of Trajectory Flexibility Preservation Impact on Traffic Complexity

“…18 Some metrics have been proposed that are independent of the airspace structure and controller perspective. For example, Delahaye et al 19 introduced complexity metrics based on traffic organization or disorder based on Lyapunov exponents. In a previous paper20, the impact of preserving trajectory flexibility was analyzed on the Lyapunovexponent-based metrics.…”