Robert A. Vivona

Operational Concept for Collaborative Traffic Flow Management based on Field Observations

*† ‡ § ** Based on field observations conducted at a wide range of airline operational control (AOC) facilities and the Traffic Management Unit (TMU) of several Air Route Traffic Control Centers , a human-centered, bottom-up approach was followed to develop a future concept of operation for local/tactical en route collaborative traffic flow management (TFM). Many operational issues were recorded for different types of flow constraints and the interaction between the TMU and AOC in dealing with these situations was observed. Several key traffic flow management issues were identified that caused inefficiencies in current operations (in terms of performance metrics such as delay, workload, equity, and user preferences), despite the best efforts of dispatchers and flow managers. The operational concept provides a framework for enhancing collaboration between TMUs and AOCs to mitigate these flow management issues. One key observation was that, due to high TMU workload, the interaction between the TMU and AOC is limited in current tactical TFM operations to addressing user concerns in extreme circumstances such as emergency and low fuel load. The concept of operation suggests extending the scope of TMU-AOC collaboration to start in the early stages of tactical TFM planning and continue through implementation.

Distributed traffic complexity management by preserving trajectory flexibility

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which ground based service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. This paper presents preliminary research investigating a distributed trajectory oriented approach to manage traffic complexity, based on preserving trajectory flexibility. The underlying hypotheses are that preserving trajectory flexibility autonomously by aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by collaboratively minimizing trajectory constraints without jeopardizing the intended air traffic management objectives. This paper presents an analytical framework in which flexibility is defined in terms of robustness and adaptability to disturbances and preliminary metrics are proposed that can be used to preserve trajectory flexibility. The hypothesized impacts are illustrated through analyzing a trajectory solution space in a simple scenario with only speed as a degree of freedom, and in constraint situations involving meeting multiple times of arrival and resolving conflicts.

A Distributed Trajectory-Oriented Approach to Managing Traffic Complexity

In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which ground-based service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. While its architecture becomes more distributed, the goal of the Air Traffic Management (ATM) system remains to achieve objectives such as maintaining safety and efficiency. It is, therefore, critical to design appropriate control elements to ensure that aircraft and groundbased actions result in achieving these objectives without unduly restricting user-preferred trajectories. This paper presents a trajectory-oriented approach containing two such elements. One is a trajectory flexibility preservation function, by which aircraft plan their trajectories to preserve flexibility to accommodate unforeseen events. And the other is a trajectory constraint minimization function by which ground-based agents, in collaboration with air-based agents, impose just-enough restrictions on trajectories to achieve ATM objectives, such as separation assurance and flow management. The underlying hypothesis is that preserving trajectory flexibility of each individual aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by minimizing constraints without jeopardizing the intended ATM objectives. The paper presents conceptually how the two functions operate in a distributed control architecture that includes self separation. The paper illustrates the concept through hypothetical scenarios involving conflict resolution and flow management. It presents a functional analysis of the interaction and information flow between the functions. It also presents an analytical framework for defining metrics and developing methods to preserve trajectory flexibility and minimize its constraints. In this framework flexibility is defined in terms of robustness and adaptability to disturbances and the impact of constraints is illustrated through analysis of a trajectory solution space with limited degrees of freedom and in simple constraint situations involving meeting multiple times of arrival and resolving a conflict.

Autonomous Operations Planner: A Flexible Platform for Research in Flight-Deck Support for Airborne Self-Separation

The Autonomous Operations Planner (AOP), developed by NASA, is a flexible and powerful prototype of a flight-deck automation system to support self-separation of aircraft. It incorporates a variety of algorithms to detect and resolve conflicts between the trajectories of its own aircraft and traffic aircraft while meeting route constraints such as required times of arrival and avoiding airspace hazards such as convective weather and restricted airspace. This integrated suite of algorithms provides flight crew support for strategic and tactical conflict resolutions and conflict-free trajectory planning while en route. Versions of AOP have supported an extensive set of experiments covering various conditions and variations on the self-separation concept, yielding insight into the system’s design and resolving various challenges encountered in the exploration of the concept. The design of AOP will enable it to continue to evolve and support experimentation as the self-separation concept is refined.

Abstraction Techniques for Capturing and Comparing Trajectory Predictor Capabilities and Requirements

ion Techniques for Capturing and Comparing Trajectory Predictor Capabilities and Requirements Robert A. Vivona L-3 Communications, Billerica, MA 01821 Karen T. Cate and Steven M. Green NASA Ames Research Center, Moffett Field, CA 94035 Recent research has increased focus on the conceptual design, development and use of airand ground-based aircraft trajectory prediction capabilities to support advanced Air Traffic Management concepts. In both the United States and Europe, the sharing of fourdimensional trajectory information between many automation systems will be necessary for successful operations. Understanding the functional and performance differences between disparate trajectory predictors is critical for enabling this system interoperability. Documented capabilities for four existing trajectory predictors were compared to identify commonalities and differences. For effective comparison, it was first necessary to abstract the prediction capabilities of each trajectory predictor. Three abstraction techniques were developed. The first separated the description of modeled aircraft behavior from the associated mathematical models used to integrate the predicted trajectory. The second defined a conceptual boundary between the trajectory predictor and its client application. The third eliminated the use of domain specific terminology. The abstraction techniques proved not only beneficial for comparing trajectory prediction capabilities, but also for defining trade-offs between the compatibility and accuracy of disparate TPs to achieve system interoperability.

A collaborative approach to trajectory modeling validation

Air service providers view the growth in future air traffic demand exceeding that of capacity, making it increasingly difficult to maintain yet alone improve the current levels of safety and efficiency. Advanced air traffic management (ATM) and flight deck decision support tool (DST) capabilities are seen as the functional enablers of the future ATM concepts needed to increase capacity by two-threefold. Such automation will provide support in flight data, metering, and conflict prediction/resolution functions to name a few. DST capabilities depend directly on the performance of the underlying trajectory predictor(s) (TP) that provide the anticipated future path of the aircraft. The accuracy of the TP is critical to the success of these DST functions. A common TP validation strategy has been developed for universal application to each element of the TP structure. The TP validation strategy is complemented by a broad database of actual trajectory recordings posted on a Web site and formatted in the extensible markup language (XML). The methodology presented here provides the process for any developer to utilize this database to validate and improve their TPs performance. This paper outlines the TP validation strategy, describes the various types of validation data provided, XML format, and tools developed.

Airborne Tactical Intent-Based Conflict Resolution Capability

Trajectory-based operations with self-separation involve the aircraft taking the primary role in the management of its own trajectory in the presence of other traffic. In this role, the flight crew assumes the responsibility for ensuring that the aircraft remains separated from all other aircraft by at least a minimum separation standard. These operations are enabled by cooperative airborne surveillance and by airborne automation systems that provide essential monitoring and decision support functions for the flight crew. An airborne automation system developed and used by NASA for research investigations of required functionality is the Autonomous Operations Planner. It supports the flight crew in managing their trajectory when responsible for self-separation by providing monitoring and decision support functions for both strategic and tactical flight modes. The paper focuses on the latter of these modes by describing a capability for tactical intent-based conflict resolution and its role in a comprehensive suite of automation functions supporting trajectory-based operations with self-separation.

TIME-BASED CONFLICT RESOLUTION ALGORITHM AND APPLICATION TO DESCENT CONFLICTS

A time-based conflict resolution algorithm was developed to resolve predicted conflicts by time shifting (delaying or advancing) one of the flights prior to conflict. This resolution approach was applied to conflicts in the complex transition phase (from Center to Terminal airspace) involving flights that are also impacted by descent and time restrictions. In order to accurately account for the complex descent dynamics, a high fidelity trajectory model was used to analyze descent trajectories and the geometry of conflicts that occur in the descent phase of flight. The development of an accurate and efficient conflict resolution solution needed an accurate and simple analytical approximation of the descent trajectory. Therefore, linear and quadratic approximations of the trajectory model were assessed for their accuracy and ease of use in the conflict resolution algorithm. The quadratic approximation resulting in an average error of 0.05 nautical miles was more accurate than the linear approximation with an average error of 0.8 nautical miles. However, the linear approximation resulted in a simpler, and therefore more computationally efficient, closed form solution for the minimum time shift required for conflict resolution. It was shown that the time shift computed using the closed-form based on the linear approximation was extremely close to the more accurate time shift computed numerically based on the quadratic approximation. The difference was within 1 second (corresponding to about 0.1 nautical miles) for a relative course angle range between 30 and 150 degrees and under different descent speed profiles. The deviation increased marginally as the conflict occurred closer to the bottom of descent but the increase due to the conflict altitude was negligible. The conflict resolution algorithm and its analysis were applied to conflicts with a number of simplifying assumptions. Namely, the resolution is achieved by maintaining conservatively the horizontal separation requirement between an intruder aircraft with constant altitude and constant ground speed and a descending maneuver

A Cockpit-Based Application for Traffic Aware Trajectory Optimization

The Traffic Aware Planner (TAP) is a cockpit-based advisory tool designed to be hosted on a Class 2 Electronic Flight Bag and developed to enable the concept of Traffic Aware Strategic Aircrew Requests (TASAR). This near-term concept provides pilots with optimized route changes that reduce fuel burn or flight time, avoids interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a trajectory change from air traffic control. TAP’s internal architecture and algorithms are derived from the Autonomous Operations Planner, a flight-deck automation system developed by NASA to support research into aircraft self-separation. This paper reviews the architecture, functionality and operation of TAP.

Developing an Onboard Traffic-Aware Flight Optimization Capability for Near-Term Low-Cost Implementation

The concept of Traffic Aware Strategic Aircrew Requests (TASAR) combines Automatic Dependent Surveillance Broadcast (ADS-B) IN and airborne automation to enable user-optimal in-flight trajectory replanning and to increase the likelihood of Air Traffic Control (ATC) approval for the resulting trajectory change request. TASAR is designed as a near-term application to improve flight efficiency or other user-desired attributes of the flight while not impacting and potentially benefiting ATC. Previous work has indicated the potential for significant benefits for each TASAR-equipped aircraft. This paper will discuss the approach to minimizing TASAR’s cost for implementation and accelerating readiness for near-term implementation.