Metrics for Traffic Complexity Management in Self-Separation Operations

This paper presents a distributed, trajectory-oriented approach to managing traffic complexity applicable to self-separation operations. Aircraft trajectory-based operations are one of three key transformation in Air Traffic Management (ATM) necessary under the Next Generation Air Transportation System (NextGen) to handle the expected increase in air traffic. The research presented here is in support of the Autonomous Operation Planner (AOP), a NASA-developed research model of an airborne automation system built for the study of advanced distributed air-ground operational concepts. The premise of the distributed control architecture is to mitigate the controller workload as a constraint against increasing airspace capacity and to increase the capacity for separation assurance through pilots’ participation. The capacity for separation assurance is expected to increase as the traffic increases because that will introduce more pilot decision-makers for self-separating aircraft and thus adds scalability of capacity with demand. This paper presents preliminary research investigating two distributed functions that have been newly proposed, which provide long-horizon planning, thus preventing the emergence of complex traffic situations: a trajectory flexibility preservation function and a trajectory constraint minimization function. A trajectory flexibility preservation function allows the aircraft to preserve options to accommodate disturbances from factors such as other traffic or weather. The constraint minimization function enables ground-based agents in collaboration with air-based agents to impose just enough constraints to achieve separation assurance and flow management. The paper uses a simple scenario with couple aircraft due to the stage of the research, starting with anecdotal insight before moving to statistical inference in complicated situations. The example provides initial insights into the hypothesized impact on traffic complexity. It demonstrates that preserving flexibility may result in mitigating certain factors that contribute to traffic complexity.