Joachim Karl Ulf Hochwarth

Air to Ground Trajectory Synchronisation through Extended Predicted Profile: A Pilot Study

The Extended Predicted Profile (EPP) trajectory down-link standard was recently established to enable air-ground trajectory synchronisation and support trajectory based operations. This paper reports on a pilot study performed to demonstrate how EPP can be used in a ground-based trajectory prediction system on the basis of an example flight. In addition, the EPP standard is compared against the existing Intermediate Projected Intent (IPI) standard to demonstrate the improved capability of the new standard. Illustrated by means of a simulated example flight, the paper demonstrates that a significant improvement in air-ground trajectory synchronisation can be achieved with use of EPP.

Air-ground trajectory synchronization — Metrics and simulation results

It has been established that Trajectory Based Operations are a key component of future Air Traffic Management systems as currently underway in the United States with NextGen and Europe with SESAR. One of the major goals of Trajectory Based Operations is to provide participants accurate 4-Dimensional Trajectories predicting the future location of the aircraft with a high level of certainty. This is not realizable without improving the coordination and interoperability of air and ground systems. By leveraging GEs Flight Management System and aircraft expertise with Lockheed Martins Air Traffic Control domain expertise, including the En Route Automation Modernization system, a research initiative has been formed to explore and evaluate means of better integrating air and ground systems to bring airspace operations closer to the business-optimal goal in a safe and efficient manner. The two main components of this effort are trajectory synchronization and trajectory negotiation. Trajectory synchronization will essentially result in a more complete flight plan in the air and a more accurate trajectory representation on the ground, which is a prerequisite for trajectory negotiation. This paper briefly discusses the high-level trajectory synchronization algorithm and its implementation in a fast-time simulation environment that incorporates actual Flight Management and Air Traffic Control software. It then focuses on the analysis of metrics and simulation results from several case studies. The conclusion of these studies shows that implementation of the trajectory synchronization algorithm using Controller-Pilot Data Link Communications messages as well as the Automatic Dependent Surveillance-Contract service (including the Extended Projected Profile application) achieves consistent trajectory predictions between the air and ground systems.

Trajectory management driven by user preferences

The evolution of the Traffic Flow Management (TFM) and Air Traffic Control (ATC) systems towards Trajectory Based Operations (TBO) is constrained by the need to support a mixed fleet of aircraft for the foreseeable future. Trajectory synchronization and negotiation in particular are key enablers of TBO that need to take into account both the advanced capabilities in existing and future Flight Management Systems (FMS), and the limitations in performance and capabilities of legacy aircraft. Trajectory management systems will have to address the challenges imposed by this reality. Lockheed Martin and General Electric (GE) have established a Joint Strategic Research Initiative (JSRI) to develop technologies that can efficiently address the challenges of trajectory management. In this paper, we describe a user preference driven trajectory management concept that was developed under the JSRI. The idea consists of providing flight-specific cost information to Decision Support Tools (DST) used by controllers for strategic conflict resolution and schedule management. The cost of operating a flight may be decomposed into the cost of fuel and other direct and time related costs (such as crew pay, aircraft maintenance, or connecting passengers). In current operations, there is no practical mechanism to make this information known to the ground automation (or the controller) which needs to make changes to the business trajectory; moreover, much of this information is considered proprietary or sensitive by the operators, making it difficult or impossible to determine the true cost impact of modifications to the reference business trajectory. However, it is precisely the overall cost of operations that should be driving the decision process. A mechanism has been developed to extract the effective operating cost from the FMS and to make that information available to ground DSTs. Cost information is encoded in coefficients that do not reveal operator specific business strategies that may be considered proprietary. This enables the ground controller (and DSTs) to make an informed decision that may increase the likelihood of operators business objectives being accommodated, and would allow operators to better inform ATCs decisions such that the impact on the business objectives are minimized when changes are required. The encoding of cost information is made in a compact way so that communication band-width requirements are reasonable.

Operational impact of trajectory prediction accuracy on air traffic automation tools

The relationship between the accuracy of aircraft trajectory predictions and performance of automation tools which depend on those trajectories is a key element in Trajectory Based Operations (TBO) concepts. This paper includes a literature review of research concerning this relationship. In addition, a study is presented which uses predicted trajectories from the En Route Automation Modernization (ERAM) system. In laboratory simulations based on historical air traffic data collection, discrepancies are introduced between the “as flown” trajectory (based on recorded radar surveillance data) and the predicted trajectory used to provide decision support services to air traffic control. The performance of the Conflict Probe (CP) is then evaluated using established methods, and System Operating Characteristics (SOC) curves are generated at different levels of trajectory accuracy. This paper attempts to characterize and quantify trajectory prediction improvements in terms the end users can appreciate: impact to decision support tools.