Liling Ren

Trajectory Synchronization between air and ground trajectory predictors

Trajectory Based Operations is a key concept of future air traffic management systems in both the United States and Europe. An overarching goal of Trajectory Based Operations is to reduce the uncertainty associated with the prediction of an aircrafts future location through the use of an accurate 4-Dimensional Trajectory. 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 effort has been undertaken to explore and evaluate Trajectory Synchronization and Negotiation concepts that bring airspace operations closer to the business-optimal goal in a safe and efficient manner. This paper focuses on different aspects of Trajectory Synchronization concepts, including existing gaps and shortfalls, and potential approaches to resolve them. An analysis of trajectory synchronization use cases and an air-ground trajectory synchronization algorithm are presented. The simulation infrastructure incorporating actual Flight Management System and En Route Automation Modernization system trajectory predictors is discussed, including simulation results from a trajectory synchronization case study. The cases studied show that consistent trajectory predictions can be achieved between the air and ground systems through trajectory data exchange via Controller-Pilot Data Link Communications uplink and downlink messages as well as the Automatic Dependent Surveillance-Contract service, including the Extended Projected Profile application.

Small Unmanned Aircraft System (sUAS) Trajectory Modeling in Support of UAS Traffic Management (UTM)

Small unmanned aircraft system (sUAS), as defined by the FAA, refers to a small unmanned aircraft weighing less than 55 pounds on takeoff, and its associated elements that are required for the safe and efficient operation of the small unmanned aircraft in the national airspace system. The unmanned aircraft system (UAS) traffic management (UTM) system is envisioned by NASA to enable civilian low-altitude airspace and UAS operations by providing services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning and rerouting, separation management, sequencing and spacing, and contingency management. Trajectory modeling and prediction methods are foundational capabilities in support of UTM to achieve its goals. This paper presents a framework for the development and validation of trajectory modeling and prediction methods for diverse types of sUASs under nominal environment and under a variety of realistic potential hazards, including adverse environmental conditions, and vehicle and system failures. Results from initial analysis of major components of the framework are also presented. Detailed results from the development and validation will be reported in subsequent papers as the research progresses.

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.

Cloud computing for Air Traffic Management - Framework analysis

This paper presents a framework for transitioning Air Traffic Management (ATM) functions to cloud computing, for cost savings, and gains in performance and efficiency. With the established framework, initial analysis was carried out for NAS automation systems. The analysis revealed that it is technically feasible to transition most of the ATM functions to the cloud computing environment, with benefits significant to both the system owner and NAS end users. A study of recent development in the field also revealed that, while challenges exist, with the proper alignment of technical and investment decisions, transitioning of ATM functions to the cloud computing environment can be achieved much faster, and that it is already happening.

Small unmanned aircraft system (sUAS) categorization framework for low altitude traffic services

Within the context of unmanned aircraft system (UAS) traffic management (UTM), an small UAS (sUAS) categorization framework has been established for low altitude traffic services to enable safe and efficient sUAS operations. This is achieved on the foundation of understanding the existing manned aircraft, model aircraft, and UAS categorization methods, and the effects of sUAS design and operational characteristics on the trajectory of the sUAS itself and interactions the sUAS may have with the environment, other aerial vehicles, people, and structures on the ground. The framework includes categorization methods for each of the following aspects: aircraft configuration, type of flight, flight rules, performance-based navigation (PBN) capabilities, flight and operations control, and vehicle flight performance. Initial criteria for the categorization methods were discussed along with additional analysis needs to improve and refine the framework.

Transformation of Mission-Critical Applications in Aviation to Cyber-Physical Systems

This chapter provides an in-depth analysis of mission-critical applications in aviation that involve the decision triad of aircraft, Flight Operations Control (FOC), and the Air Navigation Service Provider (ANSP). A characterization of operations and system requirements is carried out to provide bases for identifying cyber-physical system (CPS) transformation opportunities. Transformation opportunities are examined from the perspectives of the aircraft, the FOC, and the ANSP respectively. Benefits provided by the transformation and the challenges faced by this transformation are discussed, with potential path for addressing them identified. It is concluded that CPS integration is already happening in some segments, and ultimately an industry-wide transformation can be achieved.

UAS sense and avoid and TCAS interoperability

Collision Avoidance for General Aviation Thomas Billingsley, Lincoln Laboratory, MIT • Model CA as Markov Decision Process (MDP) • Encode performance constraints of GA • Optimize for total overall expected cost: — Near mid-air collision, alert, resolution reversal Decomposition Method for Optimized CA with Multiple Threats James Chryssanthacopoulos, Lincoln Laboratory, MIT • Pairwise vs. global • Extend MDP to pairwise decomposition — Command arbitration: optimal pairwise action — Utility fusion: optimal pairwise utility (e.g. max-sum)

Off-nominal trajectory computation applied to unmanned aircraft system traffic management

An Unmanned Aircraft System (UAS) Traffic Management System (UTM) relies significantly on automation, introducing the need for efficient and accurate trajectory computation to enable coordination and safety. The main objective of this paper is to present and to organize prior work and relevant concepts with the goal of developing a framework for UAS trajectory prediction in the presence of anomalous events. Literature documenting UAS safety and risk assessment has provided multiple pointers for identification and characterization of system failures that cause trajectory deviations or changes to its associated qualities. A UAS trajectory modeling framework considering endogenous and exogenous factors affecting the trajectory is introduced and used in this exposition. In addition, a general formulation of the trajectory computation challenge is presented along with key requirements for potential solution approaches.

Cloud Computing for Air Traffic Management - Cost/Benefit Analysis

A study of recent developments in the field of cloud computing indicates that, while challenges exist, with the proper alignment of technical and investment decisions, transitioning of Air Traffic Management functions to the cloud computing environment can be achieved much sooner than one would perceive, and that the transition is already happening for applications in air transportation. This paper demonstrates a framework for transitioning Air Traffic Management functions to cloud computing, for cost savings, and gains in performance and efficiency. An application modeled after a dynamic flow management system was used in a case study to identify required system changes and the associated cost. An analysis of the operating cost of the application revealed that significant savings can be achieved through this transition, along with the ability to benefit future upgrades and developments.