Literature Review. HALA!-PhD Management Plan. Deliverable D4. February 2012 HALA! RESEARCH NETWORK

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1 Application of the Theory of Formal Languages to the Modeling of Trajectory Uncertainty and the Analysis of its Impact in Future TBO Literature Review HALA!-PhD Management Plan Deliverable D4 February 2012 HALA! RESEARCH NETWORK Document Type: Author: Date: Distribution List: Literature Review Enrique Casado 29-Feb-12 Attn. Dr. Arnab Majumdar; Dr. Thomas Feuerle; HALA! Research Network CC. Dr. Colin Goodchild; Dr. Miguel Vilaplana

2 Change Control Version Date Revised by Description Oct-11 Enrique Casado Document initiated Dic-11 Enrique Casado Trajectory Based Operations description included Dic-11 Enrique Casado Relevant aspects of trajectory management included Jan-12 Enrique Casado Description of the trajectory synchronization process Jan-12 Enrique Casado Architectures of advanced Trajectory Predictors Jan-12 Miguel Vilaplana Colin Godchild Initial Review Jan-12 Enrique Casado Trajectory prediction models Feb-12 Enrique Casado Trajectory prediction errors Feb-12 Enrique Casado Uncertainties in trajectory predictions Feb-12 Enrique Casado Introduction and conclusions Feb-12 Miguel Vilaplana Colin Godchild Document Review Feb-12 Enrique Casado Intent Uncertainties Feb-12 Miguel Vilaplana Colin Godchild Final Review Feb-12 Enrique Casado Minor changes and updates Sept-12 Enrique Casado Typo corrections and minor updates Author: Enrique Casado

3 Index of Contents Index of Figures... ii Index of Tables... ii Executive Summary... iii 1 INTRODUCTION The future ATM system The role of trajectory predictions in the future ATM system Impact of uncertainty in the advanced decision support tools Outline of the remainder of this document TOWARDS A NEW ATM PARADIGM Single European Sky initiative in Europe SESAR (SES ATM Research) Next Generation Air Transportation System initiative in USA Discrepancies between SESAR and NextGen TRAJECTORY MANAGEMENT Automation tools in the future ATM system Trajectory Synchronization and Negotiation TRAJECTORY PREDICTION Trajectory Prediction Models Behavioral Model Aircraft Intent Description Language HYBRIDGE approach TP Errors Impact of the TP errors TRAJECTORY PREDICTION UNCERTAINTIES Weather Uncertainty Wind uncertainty Intent Uncertainty CONCLUSIONS ANNEX A ABBREVIATIONS & ACRONYMS... A-1 ANNEX B REFERENCES... B-1 Author: Enrique Casado i

4 Index of Figures Literature Review Figure 1 SESAR Performance targets... 7 Figure 2 SESAR Master Plan Overview... 8 Figure 3 NextGen Community Model... 9 Figure 4 Business Trajectory Lifecycle Figure 5 Possible types of information that can be shared to achieve trajectory synchronization Figure 6 AP16 Common Trajectory Predictor Architecture Figure 7 HYBRIDGE trajectory prediction architecture Figure 8 FMS architecture, CTAS architecture and sources of errors Figure 9 Definition of along-track, cross-track and vertical errors Figure 10 Trajectory prediction uncertainty ellipses Figure 11 Vertical buffers for FMS descents Figure 12 Probability density of actual vs. scheduled take-off times Index of Tables Table 1 4 Stage Model of human and systems information processing Table 2 Maneuver Description based on Behavioral and Mathematical modeling Table 3 Error sources vs. Impact Author: Enrique Casado ii

5 Executive Summary Literature Review This document includes a broad literature review of the technologies and methodologies used for the description and management of trajectory uncertainty, which is the first output of the PhD program entitled Application of the Theory of Formal Languages to the Modeling of Trajectory Uncertainty and the Analysis of its Impact in Future Trajectory-Based Operations as defined in the Research Plan (D3). The literature review aims at summarizing the state-of-the-art of the technologies that will support the concept of Trajectory Based Operation (TBO) with especial attention to those used for identifying the uncertainty sources that could influence the operational procedures. TBO represents the future ATM paradigm which will be implemented both in Europe and in US for managing the increasing air traffic demand in a more efficiently manner. Currently, the ATM system is based on a tactical airspace management that has to cope with a high congested environment. The expected future ATM system will try to organize the air traffic strategically, delivering as much as possible the user s preferred trajectories while maintaining at the same time the safety of operations. This new approach will require the design and development of advanced automation tools that will enhance the current capabilities with the application of new methodologies that support the new procedures. This literature review includes a general description about the changes in the ATM system required to achieve the expected modernization. It is also presented the main features of the trajectory management procedures which are considered the cornerstone of the envisioned paradigm. For such purposes, new tools capable of understanding, sharing and modifying the trajectory information are now being developed and validated. In most cases, these tools make use of trajectory predictions for delivering their own responsibilities. The influence of the prediction accuracy in the performance of the decision support tools is also analyzed within this document. This review poses the problematic related to any trajectory prediction regardless the applied methodology, including a classification of most relevant inherent prediction errors. These errors can be mapped with the sources of uncertainties to be considered in any stochastic trajectory prediction. A compilation of different approaches for evaluating such uncertainty are also presented. This document is the fourth deliverable (D4) defined by the HALA!-PhD Management Plan as part of the activities to be carried out under the sponsorship of the SESAR WP-E. Author: Enrique Casado iii

6 1 INTRODUCTION The future Air Traffic Management (ATM) system will shift from current airspace-based management towards a trajectorybased operation (TBO) paradigm. For supporting such new environment, advanced Decision Support Tools (DSTs) that make extensive use of predicted trajectories will be required. These tools will give support to the new system functionalities such as strategic planning and de-confliction or delegated separation assurance. For such purposes, the DSTs will require accurate trajectory predictions which allow more efficient traffic management. Currently, most of the systems rely on a deterministic formulation of the aircraft motion problem. This implies that the uncertainty related to the assumptions and simplifications considered are discarded (not considered in the outputs). The aim of the proposed PhD studies is to perform a systematic study of the sources of trajectory prediction uncertainty which will continue with the analysis of the impact of those sources in the outcomes of the automation tools. After the characterization of such sources, the following goal is to specify a formal framework for a qualitative and quantitative analysis of the effects of the identified stochastic factors. 1.1 The future ATM system TBO represents a shift from clearance-based to trajectory-based control, where the reference business trajectory (RBT) is agreed in advance between the airspace users and the Air Navigation Services Providers (ANSP). Such agreement is the output of a negotiation process which considers both user preferences and capacity-demand balancing requirements. This new ATM paradigm is characterized by a delegated aircraft-to-aircraft separation assurance and by the capability of providing the means for executing the RBT and the ability of following such trajectory without major discrepancies. With such high expectations and considering Trajectory Management as the key feature of the envisioned ATM system, the technological challenges to be solved are related to the new generation of DSTs that will enable such functionalities. These automation tools will be needed to facilitate and speed up the decision making process. In most cases, the DSTs will make used of trajectory information shared among the involved stakeholders through the system wide information management (SWIM) infrastructure. This information not only includes surveillance data (actual position and velocity), but also trajectory predictions to evaluate the performances of a specific flight or set of flights and to propose actions over it/them if safety can be jeopardized. The problem to be addressed is how reliable the predictions need to be considering the information about the current aircraft state and other additional data regarding the remaining of the flight. The accuracy of such information will determine the effectiveness of the Air Traffic Control (ATC) directives issued for optimizing the traffic in a sector or for avoiding possible losses of separation. 1.2 The role of trajectory predictions in the future ATM system The DSTs will be designed to help Air Traffic Controllers (ATCO), and even the flight crew, to execute their responsibilities efficiently and, more important, safely. For that purpose, automation tools will require to manage accurate information with known levels of inaccuracy. The lack of accuracy is caused by different reasons: shortcomings in the shared data, obsolete information, transmission errors In all cases, the result is an increase of the uncertainty related to any prediction used in the decision making process. Although uncertainty is an avoidable element that intrinsically cannot be removed from any prediction, it is possible to evaluate its impact managing it in a comprehensive and structured manner. The prediction of an aircraft trajectory is a well known problem that has been study since years. It can be posed as the mathematical problem of calculating the aircraft motion applying the Newton s second law. Such description commonly implies the assumption of a very constraining hypothesis: the transformation of the real aircraft motion problem into a deterministic problem. Future progresses of an aircraft are obtained as a function of current state, estimation of pilot/fms Author: Enrique Casado 1

7 intent, weather forecasts and aircraft performances. In this approach, the uncertainty is not considered although it has a relevant influence in the predictions. There are different alternatives for evaluating the uncertainty that should be taken into account by DSTs which requires such information for providing their own advisories. However, there is not a comprehensive framework where all sources can be analyzed and their effects can be evaluated globally. Many studies are focused on modeling wind uncertainties which is one of the most important sources of uncertainty, but a thorough and systematic approach is required for including other sources which also produce discrepancies between the actual and the predicted trajectories. 1.3 Impact of uncertainty in the advanced decision support tools Trajectory predictions will be the input required for the DSTs to execute the conflict detection and resolution activities, to schedule and sequence the traffic merging at a metering fix point or, in general, to optimize the system performances. It is expected that the more accurate predictions the more efficient traffic management. However, trajectory predictions are inherently affected by the uncertain information using for calculating them. Depending on the type of information used, the level of outputs accuracy obtained will be different. For example, it is better to know the real intended trajectory with the highest detail than just to make use of the flight plan information. The uncertainty associated to the inputs and to the modeling criteria will determine the quality of the outputs generated by the DSTs. High uncertain outputs will derive in less effective ATC directives, and therefore, in a less optimum traffic flow. This is the reason why the knowledge about uncertainty becomes crucial in the development of the advanced automation tools. 1.4 Outline of the remainder of this document Section 2 introduces the concept of TBO, exposing the reasons that support the need of an ATM paradigm shift and the main differences with the current one. The two main initiatives which aim at implementing this new approach, Single European Sky ATM Research (SESAR) in Europe and NextGen in US, are summarized with especial consideration to those elements which are common for both. Section 3 details the trajectory management procedures which will be the cornerstone of the TBO. The term trajectory will be differentiated depending on the look-ahead time. According to this, several trajectory stages will be described. The concepts of Business Shared Trajectory (BST) and Reference Business Trajectory (RBT) will be introduced and their relevance throughout the trajectory lifecycle. This section also presents a brief description of the automation tools required for supporting the trajectory management procedures, as well as a high level definition of the air-ground trajectory synchronization process over which the DSTs will rely on. Section 4 analyzes in detail different technologies that are currently used for predicting aircraft trajectories. Three prediction models are reviewed exploring their strengths and weaknesses regarding the requirements of the client DSTs. This section also summarizes the most important prediction errors that are introduced by the models, assumptions and simplifications applied for prediction purposes. Section 5 explains the importance of the uncertainty in the process of trajectory prediction and how this information can be treated in advance for improving the capabilities of the DTSs which uses these predictions as input of each native processes. The modeling of the sources of uncertainty is also exposed, including the description of certain distributions based on the analysis of real data, e.g. wind uncertainty. Section 6 provides the conclusions of the document. After reviewing intensively the current state-of-the-art, it is clear that a complete definition of a framework capable of integrating all uncertainty sources would add sound benefits to the efficient implementation of the TBO concept. This framework would be influenced by the characterization of the uncertainty sources because they are the responsible elements which add the stochastic behavior to the deterministic mathematical modeling of the aircraft motion. Author: Enrique Casado 2

8 2 TOWARDS A NEW ATM PARADIGM It is well known that the current ATM system is reaching its maximum capacity both in US and Europe and that it is suffering from much inefficiency that produce an increasingly unacceptable burdens on the operational costs of the users. The NextGen and SESAR initiatives are trying to solve these drawbacks by shifting to a TBO paradigm, with advanced automated systems supporting humans in managing traffic safely and efficiently. TBO is expected to bring substantial and tangible benefits to the global ATM system. The FAA has estimated that the application of the TBO concept will report a short-term cumulative benefit until 2018 equivalent to $23 billion due to a reduction in the time delays of 35% regarding current values. This would imply an associated reduction of fuel consumption about 1.4 billion gallons, and therefore, a decrease in CO2 emissions of 14 million tons during the mentioned period [1]. Although these figures are promising, the major advantages of the new system are expected in the long-term. The European Commission estimates that air traffic demand in Europe will grow to approximately 25 million of commercial flights yearly by 2050, compared to 9.4 million in 2011, and has established ambitious performance targets for that year, with a maximum delay of 1 minute per flight, a reduction of 75% in CO2 emissions per passenger and kilometer and 90% in NOx emissions and with less than one accident per 10 million flights, considering a heterogeneous traffic mix of manned and unmanned aircraft [2]. To solve this problem, the ATM community has agreed to shift the paradigm from an airspace focused management towards a trajectory based management. This transformation relies on the concept of TBO which represents the new processes and procedures that will support the capability of flying a previously negotiated trajectory taking both operator preferences and optimal airspace system performance into consideration. Nowadays, the ATM system establishes the airspaces structures, including the definition of airways and routes to be use to accommodate the traffic flow. The design of such airspace structure has to be adapted continuously to the variable demand with the subsequent effort of airspace sectors reorganization in accordance with to the foreseen needs. Once this structure is frozen, the next step is to match the flights with the available capacity. This is the key element of the process because only a certain number of flights within the same sector can be safely handled at the same time. The maximum number of flights that can be safely handled determines the maximum capacity of the airspace volume, which is directly related to the workload perceived by the ATCO responsible of facilitating the planned traffic flow. The ATCOs are responsible for delivering the expected service while ensuring the operational safety which basically is equivalent to ensure that the separation minima among aircraft are not breached in any case. The design and organization of the airspace based on these limitations are mainly driven by the prediction of the traffic 1 flow made by the ground based systems. The influence of the prediction process on the airspace organization is highly significant. The ground based trajectory predictors use the information contained in the flight plan to calculate the expected aircraft trajectory. This process does not make use of any relevant information about the user preferences which would increase the accuracy of the predictions. Thus, the trajectory predicted by the ground infrastructures, which is used to define the airspace demand, does not represent accurately the users optimal trajectories. This situation provokes an inefficient use of the airspace while increases the users operational costs as much as the difference between the desired trajectory and the actual trajectory is. These discrepancies affect the design of the airspace during the planning phase because drops the expected capacity, and also produces a reduction on the system performance due to airspace structure reorganizations. The impact of the current approach is a less optimized use of the resources and a high inflexible system to cope with unexpected events. The procedures applied by ATCOs to manage the traffic flow within the airspace under their responsibility are based on the idea of conflict free handover. This means that it is possible to release indications to any flight with the only objective of delivering to the downstream sector a traffic flow without any infringement of the separation minima between flights. The ATCOs only look at a small part of the trajectory contained within the considered sectors and assume decisions over the 1 In the current system, there is a huge mismatch between the predictions made by ground systems and by onboard flight management systems (FMS). The FMS is able to generate accurate predictions of future aircraft states because it manages all relevant actual and forecasted information. However, the ground automation tools do not have the same level of information especially that related to the aircraft intent. Author: Enrique Casado 3

9 aircraft evolution without evaluating the impact on the further aircraft states rather than the separation with the surrounding traffic. The tactical interventions issued by the ATCOs do not usually pay attention to their influence in the remaining of the trajectory. This situation derives in higher discrepancies from the optimal trajectory and huge prediction deviations. The impact has to be analyzed not only for any intervened flight but also for all the downstream traffic. The decision applied for managing the whole traffic in the following airspace sectors will affect the surrounding traffic in the actual and future sectors, and therefore, all the outputs computed by the automation tools will become invalid and will have to be recalculated. The alternatives for overcoming these circumstances, and therefore increasing the ATM system capabilities, is the implementation of the TBO paradigm, which leans on two basic elements, the definition of the business trajectory and the ownership of such trajectory. The business trajectory is the description of the sequence of aircraft states that represent the aircraft movement according to the user preferences and airline business strategies. This trajectory also takes into consideration the operational context where the flight is going to be operated to determine the expected aircraft behavior with time. Modifications on the business trajectory, however necessary, will inevitably impact the foreseen cost effectiveness of the operation. In the future ATM environment, the trajectories should stay untouched as much as possible while no safety parameters are violated. Any possible modification or update will be analyzed in advance to determine both the effects on the airspace sector where the aircraft is currently flying and also on the downstream traffic. The second element is the ownership of the business trajectory. Each airspace user is the responsible agent of generating the expected trajectory which fits the best its business goals. Once this trajectory is agreed with the ANSPs, it is considered as contractual conditions that have to be respected while no safety issues prevent it. This information has to be available to any interested stakeholder who needs it for elaborating its own plans or for providing advisory indications to other stakeholders. In this scenario, the aircraft will be operated according to the previously agreed business trajectory, ensuring that the deviations from the nominal path are always within predefined boundaries. Since no special circumstances other than the expected are faced by the aircraft, the execution of the actual trajectory will be very close to that generated during the planning phase. The flight crew will be in charge of maintaining these operational requirements, while ATC will monitor that the whole traffic is delivered conflict free, avoiding unnecessary over-constraints. This new conception of the ATM system based on trajectory management needs to be supported not only by new processes and procedures, but also by the development of an infrastructure of automation tools capable of enabling the new required features. There are many foreseen activities that will be performed automatically by the automation tools, decreasing the ATCO s workload, and therefore, optimizing the system resources. Such tools will facilitate the process of describing, negotiating, sharing and modifying the business trajectory which is the core element to be managed under the future ATM paradigm. These mechanisms will be supported by a common infrastructure where all stakeholders will be connected to and where all required information will be continuously accessible according to the credentials of each user. This infrastructure will provide the information regarding the system state which includes trajectory data of all involved (planned and actual) flights, weather forecasts or airspace organization. Any stakeholder will have the obligation of sharing the information that need to be known by others and maintaining it up-to-date. As mentioned before, two major initiatives are now ongoing, the SESAR in Europe and NextGen in USA with the goal of implementing the TBO concept by means of the development and deployment of a completely new ATM infrastructure. Both programmes pursue the same objective but with slightly different approaches due to the dissimilarities of the ATM environment in both areas. The structure of the airspace is the main difference affecting the envisioned planning for reaching TBO. Europe airspace is fragmented into multiple elements according to the number of states that belong to it. This characteristics implies that there is no a single sky as in USA, and therefore, the first step towards the new paradigm is to homogenize the European airspace trying to collect all individual fragments into a common and unique airspace. The following sections summarize the most relevant characteristics of these two main projects that will change the operational rules of the ATM system in the future years. Author: Enrique Casado 4

10 2.1 Single European Sky initiative in Europe Historically, the development of the air traffic industry in Europe has been constrained by an inflexible structure of the airspace controlled by multiple ANSPs. The airspace organization has been proved as most important obstacle for absorbing the increasing traffic demand. The EU Single European Sky (SES) is an ambitious initiative launched by the European Commission (EC) in 1999 to reform the architecture of the European air traffic management. It proposes a legislative approach to meet future capacity and safety needs at a European rather than a local level [3]. The key objectives are the restructuration of the airspace according to the expected air traffic flows; the creation of additional system capacity to cope with the increasing demand; and the improvement of the system efficiency by the optimization of the available resources. The SES project promotes an airspace organization based on the definition of Functional Airspace Blocks (FABs) instead of national borders. These functional blocks will be designed dynamically according to the foreseen air traffic flows to be managed within. The FABs concept was developed in the 1 st Legislative Package of the SES (SES I 2 ) as one of the main means for reducing European airspace fragmentation. The idea behind this new concept is to avoid losses of efficiency due to an airspace organization constrained by the national airspace boundaries. FABs support the strategy of managing air traffic in an integrated manner, by merging several portions of national airspace into wider blocks. Within each FAB, air traffic flows and air navigation services will be coordinated and managed according to the actual operational needs, resulting in significant capacity gains and in a more efficient airspace use across Europe. However, the SES legislation needed to be improved to deal with performance and environmental challenges and to define the operational targets that the future ATM system should deliver. In 2008, the SES 2 nd Legislative Package (SES II) was released to ensure a more sustainable and safer development of the SES concept. The main objectives of this additional legislation were enclosed in five different areas: - Implementation of a Performance Scheme, which provided indicators and binding targets on the key performance areas (KPAs) of safety, environment, capacity and cost-efficiency whereby required safety levels are fully achieved and maintained. - Integration of service Provision, which supported the implementation of FABs by extending the scope to lower airspace up to the airport and clearing national legal and institutional obstacles. - Network Management, which implemented a set of rules to ensure optimal management of the European ATM network and provide global interoperability and cooperation. - SES Safety Framework, which enhanced the competences of European Aviation Safety Agency (EASA) to the aerodromes and Air Traffic Management / Air Navigation Services. - Deployment of new technologies, which established the framework for a coordinated technological development of airborne and ground-based systems. In 2005, The SESAR Programme was launched with the intention of fostering the research activities needed for delivering the advanced technologies that will support the deployment of the SES. - Management of Airport Capacity, which defined an action plan with several measures to increase the output and optimize the planning of airport infrastructures, while at the same time raising safety and environmental standards. 2 The 1 st legislative package, adopted in 2004, provides the basis for a more efficient ATM system with higher capacity and improved interoperability. The package comprises the following regulations [4]: - Framework Regulation (EC No 549/2004) - laying down the framework for the creation of SES; - Service Provision Regulation (EC No 550/2004) - on the provision of air navigation services in SES; - Airspace Regulation (EC No 551/2004) - on the organization and use of airspace in SES; - Interoperability Regulation (EC No 552/2004) - on the interoperability of the European ATM network. Author: Enrique Casado 5

11 SES represents the most ambitious initiative to reform the architecture of the European ATM environment to meet future capacity and safety needs. The technological developments required for such purpose will be delivered by SESAR, which will provide the advanced procedures and technologies that will shape up the implementation of the new ATM paradigm in Europe SESAR (SES ATM Research) As part of the SES initiative, SESAR represents the technological developments required to support the implementation of the new ATM operational concept. It will help to create the envisioned paradigm shift, making use of state-of-the-art and innovative technologies. The aim of SESAR is to provide a high-performance air traffic control system capable of ensuring the safe and environmentally sustainable development of the European air transport. Most of the systems that are now in use need to be re-designed or even deprecated because they do not provide the required performances. To alleviate this situation, a huge research effort has been planned. These innovative tasks aim at developing new generation technologies that will be the core of the expected ATM system capabilities. SESAR gathers and coordinates all these technological activities, heading them to the common goal of implementing an ATM infrastructure in Europe that meets the defined improvements in system capacity, operational safety and environmental impact. The programme is composed of three phases: - Definition Phase ( ). The main delivered outputs have been the definition of the Performance Targets to be addressed, the definition of the Concept of Operation (ConOps) and the ATM master plan which defines the content, the development and deployment plans to be executed. - Development phase ( ) The required advanced systems, components and operational procedures will be produced in accordance with the SESAR ATM Master Plan and Work Programme. - Deployment phase ( ). It describes the large scale production and implementation of the new ATM infrastructure. To evaluate how well the future system will deliver the expected services, there have been established targets for each of the KPAs 3. These values will be used to analyze the global performance of the system and its achievements towards the envisioned ATM environment. The system should be able to cope with a three-fold traffic in 2020 (from 2005 baseline), reducing at the same time the on-ground and airborne delays (KPA Capacity target). Considering the anticipated increase of air traffic flow, the system has to ensure an improvement factor of ten in the overall safety (KPA Safety target). Both targets have to be achieved while also reducing the fuel consumption and the associated noise and gas emissions (KPA Environmental Sustainability target), with a decrease of a half of the total gate-to-gate costs (KPA Cost-Effectiveness target). A complete definition of the targets described for each KPA, including a description of the mid-term (2020) and longterm (beyond 2020) objectives and the mechanisms and strategies to reach them can be found in [5]. 3 The ICAO KPAs are grouped in three different categories according to the relevance of the expected impact of the associated improvement: societal (Safety, Security and Environmental Sustainability), operational (Capacity, Predictability, Efficiency, Flexibility and Cost-Effectiveness) and enablers (Access and Equity, Participation and Interoperability). The KPAs Efficiency, flexibility and Predictability are considered as Quality of Service indicators of the system. Author: Enrique Casado 6

12 Figure 1 SESAR Performance targets Once the high level targets related to the expected improvements of the system performances were defined, the next step was to define the operational concept that will support the consecution of such objectives. The SESAR ConOps [6] describes the major features that are needed to enable the planned system capabilities. There are two main system features that can be considered as necessary foundation of the others: the System Wide Information Management (SWIM) network and the Collaborative Decision Making (CDM). The former will replace the current point-to-point data systems by a middleware based data network where all stakeholders will be connected at any time. This hardware and software infrastructure will be used for disseminating the relevant information among the ATM community. The communication protocols 4 will allow each actor to publish or receive the information according to their own responsibilities. The latter represents the processes, procedures and tools capable of taking actions on the system performances based on the information shared through SWIM. Some of those CDM elements are now in use at some airports, but the idea is to enhance its usability to any phase of the trajectory management from the early planning until the actual execution. CDM will harmonize the requirements and needs of the stakeholder in a collaborative manner, enabling the interaction among all interested actors when an action on a trajectory has to be taken for the global benefit of the system. This new approach will describe the mechanisms for planning, managing and updating the aircraft trajectory using the CDM as tool for integrating all stakeholders requirements, preferences and system needs. For that purpose, new separation modes and automation tools require to be developed to ensure the proper situational awareness of pilots and ATCOs, maintaining at the same the respective workload below a defined threshold. This infrastructure will facilitate the trajectory management activities that are the essence of the future ATM paradigm. These activities will be focused on the use of precise trajectory data to improve predictability and increase system capacity. For the implementation of the expected concept of operation, it has been required the definition of a detailed plan where all technological improvements are organized according to their relevance and mature. This plan includes the coordination of associated research and development (R&D) efforts among all involved stakeholders. The SESAR Master Plan [7] represents the global technological roadmap that will deliver the operational improvements expected for transitioning the current system to the envisioned ATM environment. This Master Plan organizes the transformation into six evolving ATM Service Levels (0-5) depending on the date at which the corresponding capabilities can become operational. It also includes a timeline describing the expected improvements and technological readiness for each of the operational improvements defined and a general overview of the R&D framework that will support the developments. 4 The network will rely on a middleware capable of managing the information accessibility according to the credentials of each user. The communication mechanisms will be based on publish/subscribe and/or request/reply protocols. Author: Enrique Casado 7

13 Figure 2 SESAR Master Plan Overview The responsibility of managing this plan is on the SESAR Joint Undertaken (SJU) [8], whose objective is to execute the Master Plan ensuring that the final aim of deploying an advanced ATM infrastructure is delivered on time and within the funding constraints. The SJU is a Public-Private Partnership (PPP) that includes Eurocontrol, the EU, the European industry, ANSPs and airport organizations. SJU is the responsible organization in charge of coordinating all the individual projects for obtaining the appropriate technical and operational improvements. All research activities will be organized in accordance with the Master Plan and will be executed following the requirements established by the SESAR ConOps. 2.2 Next Generation Air Transportation System initiative in USA Different than in Europe, in USA the problems associated with the fragmentation of the airspace and the diverse national authorities do not exist. The National Airspace System (NAS), which is the organization that owns the ATM infrastructure, defines the procedures and deploys the resources that enable safe air traffic operations throughout the whole nation. This main difference between both systems implies that, although the major objective for the future ATM systems is similar or even equal in some aspects, the way to achieve it presents other requirements in USA. The increase of the air traffic demand during the forthcoming years, and the need of performing more efficient and safer operations summarize the vision of the future ATM system. Such system will cope with those problems integrating all stakeholders into a centric data network and facilitating as much as possible the execution of the user preferred trajectories. The paradigm shift required to do this is identical to that required in Europe, and therefore, regardless the development and implementation strategies, the interoperability has become a paramount element to be considered during the whole process in both initiatives. The system will incorporate information about users preferences which represents a huge modification regarding the current situation. This information will have to be available in advance to all stakeholders to ensure that any modification of the business trajectory will consider them. For an efficient decision making process, not only information about how the users would wish to operate their flights but also weather forecasts, status of the airspace and standard procedures have to be fully accessible through the deployed network. Author: Enrique Casado 8

14 In June 2007, the Joint Planning and Development Office (JDPO) [9] released the Concept of Operations [10] and Enterprise Architecture (EA) [11] that defines the master lines of the design and development of the Next Generation Air Transportation System (NextGen). The NextGen ConOps describes how the system will work from an operational standpoint and will provide an overall, integrated view of future operations, including the definition of the key transformations from today s operations. The EA, commonly referred to as the blueprint for NextGen, describes the segments, capabilities, operational activities and relationships to the key target components of NextGen in the year The EA defines how these capabilities fit together, and it is intended to be used as a tool for planning, negotiating and understanding the dynamic, interrelated business processes and technical solutions that impact the aviation community. Figure 3 NextGen Community Model NextGen involves not only the development of new technologies, but also the leveraging of existing ones. This includes satellite navigation, advanced digital communications and enhanced connectivity between all participants of the air transportation system. However, the most relevant research effort will be focused on developing the new capabilities that will support the envisaged transformation. Figure 3 depicts how these new capabilities will be integrated into the global system. - Aircraft Trajectory Based Operations. Within the trajectory-based airspace, all trajectory management functions across all time horizons are based on the aircraft s 4D trajectories. The use of this precise information should dramatically reduce the uncertainty of aircraft s future flight path, in terms of predicted spatial position (latitude, longitude, and altitude) and times along points in its path. - Performance Based Services. There are multiple service levels aligned with specified user performance thresholds to provide choices to users depending on needs, required communication, navigation and surveillance performance, environmental performance criteria, security parameters, etc. Services are flexible according to the situation and consolidated needs of the users. Author: Enrique Casado 9

15 - Weather Assimilated into Decision-Making. Common service integrated into the centric network capable of disseminating real-time weather measurements, forecasts and history to be used by any stakeholder. - Dynamic Airspace Configuration. Dynamic organization of the airspace that provides the capability of balancing the actual demand with the available system capacity while meeting changing constraints of weather, traffic congestion and complexity. - Super Density Operations. The specific airspace configurations or routes chosen in near-real time to provide flexibility and maximize arrival and departure throughput. - Equivalent Visual Operations. This represent the capability to provide the aircraft with the critical information needed to maintain safe distance from other aircraft during non-visual conditions, including a capability to operate at levels associated with VFR operations on the airport surface during low-visibility conditions. - Layered Adaptive Security. The security system is constructed in layers of defense to detect threats early and prevent them from meeting their objective while minimally affecting efficient operations. - Position, Navigation and Timing (PNT) Services. A service that enables the ability to accurately and precisely determine one s current location and orientation and desired path and position; apply corrections to course, orientation and speed to attain the desired position; and to obtain accurate and precise time anywhere. - Network-Enabled Information Access. This infrastructure will allow seamless information sharing among stakeholders, who will provide information relative to air navigation service, airport, flight operations, shared situational awareness, security, safety or performance management services. Similar to the SESAR Master Plan, the JPDO has also released a global plan to steer the technical modifications, improvements and developments throughout the established timeframe. This plan is exposed in the Integrated Work Plan (IWP) document [12]. The IWP intends to be a master planning document that depicts the collaborative stakeholder s efforts that are needed to implement the vision described in the ConOps and EA. The aim is to gather comprehensive information about the elemental operational improvements, enablers, development and research milestones, as well as policies needed to make operational the NextGen initiative. 2.3 Discrepancies between SESAR and NextGen Although the main objective of both programmes is the same, the transformation of the current ATM paradigm into a new one based on trajectory management, there are dissimilarities between them mainly due to different approaches to achieve this major goal. Besides, these two solutions include different strategies to transitioning the current technologies to the new required ones. The need of establishing proper rules for managing equipped and non-equipped aircraft during the interim phase has also been addressed differently. Next, the most relevant topics that make SESAR and NextGen slightly different are listed: - The timeframes of both programmes are different, 2020 for SESAR and 2025 for NextGen. - SESAR is only focused on the development of the ATM infrastructure, while NextGen considers other elements that could have influence in the final system, such as Homeland Security. - The approach followed by SESAR is assuming a Gate-to-Gate scope that can be considered as an Enroute-to- Enroute view including the turn-around process. NextGen enhances this approach by including all aspects of the airport terminal and passengers operations, adopting a Curb-to-Curb scope. - Safety and Environmental Impact are relevant elements that are detailed by NextGen ConOps, while SESAR evaluates them in a rough manner measuring their impact through the related KPA. Author: Enrique Casado 10

16 - The technological development supported by SESAR JU is ahead in data communication 5, while NextGen is ahead in defining the use of the Automated Dependant Surveillance Broadcast (ADS-B) Out. - The acquisition and sharing of the information related to weather forecasts and its use throughout the global community differs in both cases. In NextGen, this information will be provided by the National Oceanic and Atmospheric Administration (NOAA) which is the scientific agency within the Department of Commerce focused on the study of the conditions of the oceans and the atmosphere, while in SESAR the weather information provision is considered outside of its scope of work (even more than having an unique source of information, the first approach would be to have a wide range of atmospheric data sources). - During the development phase of SESAR, institutional barriers (property of data) will need to be mitigated through any kind of regulation. This is a prerequisite to be established in advance to the exchange of information supported by the SWIM network. This is not the case of NextGen because all participating agencies belongs to the same nation which is the only responsible state involved in the project. Although these differences can produce some divergences in how the new ATM paradigm will be deployed, there is still a common vision of the future system. This is the reason why a framework for a cooperative collaboration was agreed in March This agreement defines rules on issues such as governance, intellectual property rights, reciprocity and liability. It was formalized in a memorandum of cooperation in civil aviation research and development which enables the EU and the USA to jointly pursue their common objective of developing and deploying a greener and more efficient air transport systems through a legally binding cooperation framework, based on commonly agreed reciprocity principles. In accordance with these agreed reciprocity principles, both parties undertake to identify the opportunities available to each other's stakeholders to contribute to enhance the projects of equivalent research and development activities. 5 Europe was the first in making use of the Controller Pilot Data Link Communications (CPDLC), with 15 airlines using the service via the first operational implementation in the Maastricht Upper Area Control Centre (MUAC). Author: Enrique Casado 11

17 3 TRAJECTORY MANAGEMENT Literature Review The future transformation of the ATM system is based on the applicability of the TBO paradigm. This new approach for air traffic operations relies on the capability of providing the means for executing the agreed trajectory and the ability of following such trajectory without relevant discrepancies. The provision of the appropriate infrastructure is under the responsibility of the ANSP organizations, while the adequate execution of the trajectory depends on the aircraft and the flight crew. Trajectory Management (TM) encompasses the process and procedures that establishes how this provision and execution have to be performed. This also includes the roles and responsibilities of all involved actors according to their respective levels of involvement and the mechanisms for trajectory planning, negotiation, updating and reviewing [13]. There are several stages, form the planning until the execution, during which the trajectory can be modified due to a change in the airspace conditions or a user requirement. Thus, there are different descriptions of the trajectory according to the accuracy of the information and the considered timeframe. SESAR considers the following classification as base for a common understanding: - Business Development Trajectory (BDT), which is the trajectory planned in the earliest stages and initially shared with the airspace community through SWIM. - Shared Business 6 Trajectory (SBT), which is the trajectory published by the airspace user for collaborative ATM planning purposes. - Reference Business Trajectory (RBT), which is the last instantiation of the SBT. The refinement iterative process of the SBT ends up with a final description of the filed flight plan. This is the trajectory that the airspace user agrees to fly and the ANSP and Airports agree to facilitate. - RBT Revision, which represents modifications over the RBT triggered by the flight crew or by the ATCO as a result of a change in the applied constraints (altitude, time, routes ) due to weather hazards, traffic flows congestions or onboard system dysfunctions. - RBT Update, which represents an update of the agreed trajectory due to a discrepancy between the trajectory predictions computed by the FMS and the trajectory shared through the network. Figure 4 Business Trajectory Lifecycle The TM procedures are established for enabling the definition of the aircraft trajectory throughout the complete trajectory lifecycle from the initial plan until its execution. TM gathers all the processes required for adding information once the knowledge about how to execute the plan has improved. These processes are represented by successive planning phases 6 For civil applications the terminology used for naming the trajectories is Business, while for military applications is Mission. The future ATM system will be able to manage both definitions according to their specific characteristics. The following sections of the document only make reference to Business Trajectories although the exposed definitions are also applicable to Mission Trajectories. Author: Enrique Casado 12

18 from long term to medium and short terms involving all ATM stakeholders who collaboratively interact to progressively build the Network Operation Plan (NOP). The NOP is a dynamic rolling plan which provides a detailed overview of the whole ATM system. The information contained in the NOP includes traffic demand, airspace and airports capacity or current airspace constraints. It can be seen as a facilitator whose aim is to catalyze the negotiation process between airspace users and ANSPs. The lifecycle of any business trajectory begins long time previously to the day of execution. As soon as the airspace user has a clear idea about the intended operations, the information is fed into the net-centric infrastructure and the negotiation process starts. The main negotiation phases, as depicted in Figure 4, are close related to the different definitions of business trajectory exposed above. Along the whole lifecycle, it is possible to distinguish the following stages: - Long Term Planning. The BDT represents the initial description of the future operation, which usually includes only information about the departure and arrival airports and day of operation. It may be generated several months or only hours before the intended departure, depending on the business model of the operator. Once the user considers that the BDT is enough detailed, the process follows with the publication of such data through the SWIM infrastructure. This initiates the collaborative planning. - Medium and Short Term Planning. Once the collaborative planning has started, the trajectory is updated according to iterative negotiation cycles. These iterations make use of the SBT whose final form is added to the filed flight plan. As the day of operation approaches, the knowledge of the constraints to be considered increases, and therefore, the variations of the SBT become less likely. During each actualization, a new improved SBT is shared among all actors, allowing rising discrepancies if some of them find a conflict with previously agreed trajectories. - Trajectory Agreement. At some point prior to the departure (e.g. 15 minutes before), the last iteration of the SBT is agreed between the aircraft operator and the ANSP and then the SBT is finally published as the RBT. The RBT represents the trajectory that the operator agrees to fly and the ANSP agrees to facilitate. The flight crew owns the responsibility of executing the RBT according to the established agreement. Due to this, the final version of the RBT is introduced by the flight crew into the NOP. This implies that any modification or update of such information will need the validation of the flight crew as owner of the RBT. However, the publication of the RBT does not represent a clearance. It is the target trajectory to be achieved, but it has to be validated progressively by ATC. To execute this procedure fluently, a robust air-ground synchronization is required. This will ensure the proper negotiation and clearances communication. - Trajectory execution, monitoring, revision and update. Once airborne, the flight crew has the responsibility of following the agreed RBT which will be cleared by ATC in a step by step basis. The clearances will be issued according to the traffic condition down flow and the likelihood of conflict-free trajectory execution. To be able to ensure this condition, ATC will make use of surveillance data and ground-based trajectory predictions. Such predictions will be elaborated based on the information shared by the aircraft through SWIM. With this information, ATC is capable of computing a predicted trajectory according to the current aircraft position and velocity gathered from the surveillance infrastructure and the planned intention of the aircraft. Based on the prediction and the knowledge of actual flight execution, ATC will monitor each RBT ensuring that they are executed within a certain precision and navigation performance boundaries, or raising a negotiation process if some threshold is overcome or an unexpected event occurs. This task is crucial to maintain conflict-free trajectories, and therefore, safe operations. The negotiation process can be triggered by an unplanned ATM constraint (RBT revision) or when there exists a discrepancy between the actual and the shared trajectories higher than a designed threshold (RBT update). These thresholds are defined in the Trajectory Management Requirements (TMR), which specify the maximum deviations from nominal values for the time and lateral and vertical profiles. In both revision and update procedures, ATC will validate the modification after evaluating the overall network impact of the new RBT. When several RBTs are revised or updated at the same time, the overall performance of the ATM will prevail over single optimum alternatives, adopting a fair solution based on the users preferences when possible. Author: Enrique Casado 13

19 3.1 Automation tools in the future ATM system It is anticipated that the TBO concept implementation described above will rely on the ability of ATC for supporting the Autonomous Aircraft Operations (AAO) concept [14], which will involve the transfer of responsibility of separation assurance from ground-based ATC to the cockpit. The improvements in Communication, Navigation and Surveillance (CNS) expected in future AAO will lead to a shared responsibility among all the involved stakeholders, mainly the flight crew, the Airline Operation Centres (AOC) and ATC, for the safe progress of the flight through the airspace. Under current paradigm, ATCOs and air traffic flow managers are viewed as a central authority with total responsibility both for short-term safety issues and long-term traffic flow scheduling. However the new paradigm will distribute these responsibilities according to the level of involvement of each stakeholder along the lifecycle of the trajectory. For providing these new functionalities, ATC will require improved and enhanced applications that ensure the safety of operations whilst enabling and supporting the distributed trajectory management. The development of the future Decision Support Tools (DSTs) will take into account the most relevant technical requirements needed for the implementation of TBO, such as, on-board self-separation capabilities, distributed conflict detection and resolution, or user preferred trajectories. These tools can be part of a wider ground-based automation infrastructure, or be included into the on-board system as well. In both cases, all these advanced applications will support the ATM actors during the continuous decision making process. The main advantage provided by them is the capability of speeding up the analysis and identification of high risk or complex situations and the associated generation of alternative solutions. The term of automation tool can be interpreted in different ways in the technical literature, from the mere introduction of computer technology where it did not exist, to the utilization of computing systems with some levels of autonomy. However, the most accepted and general definition is a device or system that accomplishes (partially or fully) a function that was previously carried out (partially or fully) by a human operator given by Wickens, Mavorm Parasuraman and MacGee [15]. Based on this definition, the automation tools that will be developed for supporting the new ATM paradigm should be applications that compensate human vulnerability but also exploit human strengths. In some cases, automation has been considered as a substitutive system of human, but this approach is not valid for the future TBO environment. These tools will have to be aligned with the concept of human-centered automation [16] which represents the environment where the actual capabilities of the controllers, such as collaborative negotiation and problem solving, are augmented and boosted; and the weaknesses, such as reduction of situational awareness due to higher traffic density and complexity, are overcome. Automation can be applied to any of the system functionalities which are closely linked to the human information processing stages. The model exposed in [17] declares four different stages that are used for describing the corresponding automation functions: Human Information Processing Stages Sensory Processing Acquisition and registration of multiple sources of information, including initial data pre-processing and selective attention. System Functionalities Information Acquisition Perception/ Working Memory Conscious perception, selection and management of processed information in working memory, including cognitive processes such as rehearsal, integration and inference. Information Analysis Decision Making Response Selection Definition of appropriate decision and action according to the perceived reality and the conclusions of the information processing. Implementation of the most suitable directives consistent with the executed information analysis and decision making process. Decision and Action Selection Action Implementation Table 1 4 Stage Model of human and systems information processing Author: Enrique Casado 14

20 Any of the described functionalities in Table 1 are suitable of being automated according to the requirements of the final user and to the desired increase of reliability and reputability. However, it is possible to develop such functionalities with different levels of automation, from the null computer assistance (Level 1) to fully automated system which does not require human intervention (Level 10) [15]. Between these two boundaries, a continuous scale including 8 more levels is defined to identify the grades of automated capabilities provided by the related system. For example, a conflict detection and resolution system capable of detecting plausible future reductions in minimum separation between two flights capable of suggesting a set of suitable solving alternatives to the ATCO could be classified as Level 4. Meanwhile, other system that applied the most appropriate solution considering a predefined criteria with lower ATCO monitoring, would be considered as Level 6 or higher. For all ATM applications, regardless their level of automation, a key requisite is the ability of dynamically exchange critical information of the actual operations. This requirement can be expressed as the capability of managing the relevant traffic flow information to support the decision making process. The question is what the critical information is and how the management process can be executed efficiently. For ensuring safe operations, the most important data required by any stakeholder involved in the process is trajectory information. For designing, executing and monitoring any ATM procedure that ensures the expected levels of safety, robust trajectory synchronization among all related automated systems is required. This trajectory synchronization (air-ground or ground-ground) can be considered achieved when the shared information between systems, that could be a complete 4D trajectory or any other unambiguous representation during a certain look-ahead time, ensures that both applications are making use of the same trajectory, regardless the level of accuracy used by each one, for predicting future traffic states and also for generating decisions in accordance with such predictions. The effectiveness of the trajectory synchronization between airborne and ground-based infrastructures, and the related predicted trajectories generated in both systems as output of the synchronization process, will facilitate the extensive use of available and emerging FMS guidance capabilities (Required Navigation Performance (RNP), 4D Area Navigation (RNAV), Vertical Navigation (VNAV) or Required Time of Arrival (RTA) Guidance) that are seldom exploited due to current ATC practices. In addition, it is expected that a more extensive use of FMS-based operations can improve the predictability of the system, and therefore, the accuracy of the ATC directives that lead to an increase of the overall system capacity. 3.2 Trajectory Synchronization and Negotiation The achievement of all envisages improvements of the future ATM system are centered in the capability of managing complex traffic flows in a more efficient and smoother fashion. To that aim, a more accurate and reliable traffic synchronization will become one of the main functionalities to be deliver by the enhanced automation tools. Traffic synchronization is concerned with the management of the all aircraft operating within a specific airspace, including queues both on ground and in the air, in order to establish a safe, orderly and efficient flow. With proper traffic synchronization, it would be possible to maintain ATC up to date continuously with the more realistic information, avoiding ineffective directives that provoke delays and decreases of global throughput. Although it is possible to discuss about many improvements that should be included in the DSTs to grant the required level of synchronization, the main features are basically a more precise aircraft trajectory prediction to be used into real-time traffic analysis and decision making; and better tools for sharing actual and planned flight data, amendments released by ATC or situational awareness information [18]. Trajectory synchronization refers to the coordination and interoperability among on-ground and on-board DSTs that make use of different trajectory information in order to detect anomalies in the traffic flow, generate automatic indications to ATC and communicate modification to the RBT. It is a dynamic process that is applied during the complete lifecycle of a flight [19]. The need of synchronization relies on the requirement of knowing the progress of actual flights by the involved aircraft and also by the ground-based tools in charge of supporting ATM/ATC activities and ensuring safe operations. The trajectory prediction generated onboard by the Flight Management System (FMS) are used for closed-loop guidance by means of the Flight Control System (FCS). On ground, the trajectories are computed for supporting scheduling, sequencing, conflict Author: Enrique Casado 15

21 detection, separation assurance and conformance monitoring activities. The disparity of functionalities between both systems means that different levels of fidelity can be managed by several systems. Although the trajectory must be for all the systems unique, the representation of such trajectory will be often different depending on the requirements of the tool that will make use of these data. In most cases, trajectory information is not fully useful and some other data require to be synchronized such as weather forecasts or unforeseen ATC constraints. Two different tools are assumed as synchronized when the predicted trajectory of both systems presents, regardless their implementations, small discrepancies 7 along the considered look-ahead period. If this condition is fulfilled, all conclusions, considerations or decisions based on this trajectory information will be assumed as valid. The challenge for an optimal synchronization is to define the set of required information considering the aim of the automation tool, the flight phase and the look-ahead time of the prediction. The most accurate and precise trajectory prediction is always performed by the FMS which will supervise the proper execution of the actual trajectory while at the same time monitors the deviations from the planned (pre-computed) trajectory. This on-board 4D trajectory could be shared with the ground-based tools to perform the traffic management activities; however, this is just information about foreseen aircraft states predicted under certain known conditions (initial conditions), weather forecast and ATC constraints. The validity of this information ends when a new weather forecast update is released or when a new ATC restriction has to be applied or removed. In such cases, the downloaded trajectory should be discarded, opening the possibility of requesting a new update to the FMS or computing a new ground-based prediction. The former alternative requires high rates of information exchange through the data link communication system, which could become sometimes very complicated due to bandwidth limitations or lost of link situations. The latter alternative could lead to a de-synchronization because, although it could be possible to use the same computational predictor, the information accessible from the ground infrastructure is not the same as used by the FMS (mainly aircraft performances and user preferences). These drawbacks can be superseded, or at least improved significantly, by the synchronization of other types of information that encodes the trajectory information in such way that can be reproduced without losing the fidelity required by the considered application. This information represents the set of inputs needed by a Trajectory Predictor (TP) for computing a predicted trajectory integrating the mathematical model that indentifies the aircraft motion subject to a certain constraints and objectives. Depending on the level of accuracy and knowledge about the planned intention, there are two different types of information that could be used for improving and enhancing the air-ground and ground-ground synchronization procedures [20]: - The Aircraft Intent (AI), which is the unambiguous description of how the aircraft will be guided during the time interval for which a predicted trajectory is computed. AI encompasses information on how the aircraft is to be operated during a certain time interval, capturing basic commands, guidance modes, and control strategies at the disposal of the pilot/fms to direct the operation of the aircraft. In the same way as the aircraft exhibits a unique trajectory as a result of the commands issued by the pilot/fms, the Aircraft Intent must be formulated so that the aircraft motion is univocally determined and results in a unique predicted trajectory. - The Flight Intent (FI), which is a description of the operational requirements and constraints that must be fulfilled by the predicted trajectory (e.g. intended route, operator preferences, standard operational procedures, applicable ATC constraints, etc). In general, the FI does not determine a unique trajectory and it is seen as a basic blueprint for trajectory prediction where the details required to calculate a specific trajectory are left unspecified. FI represents those objectives and restrictions imposed over the future expected behavior/trajectory of the aircraft. It does not specify unambiguously the aircraft motion and, consequently, there are infinite trajectories that can fulfill a given one. 7 The discrepancies between two representations of a trajectory are considered small when their influence over the subsequent actions derived from the analysis of such input is operationally negligible. Author: Enrique Casado 16

22 Figure 5 shows a high level description of a robust synchronization process based on the exchange of the aforementioned information. As it is depicted, additional information related to the initial conditions (IC) is required for computing the trajectory at both sides and to avoid higher discrepancies between predictions. This information identifies the initial aircraft state from which the trajectory is going to be predicted. In the case of sharing FI information and due to its lack of detail for closing univocally the prediction problem, additional data related to the user preferences and the operational context need to be added to the prediction process by the Intent Generation Infrastructure (IGI). The more accurate these inputs are, the lower discrepancies, and therefore, higher reliability will be obtained. Airborne Trajectory Prediction Airborne Automation System Flight Intent Pilot Intent Generation Infrastructure A Initial State (navigation) Aircraft Intent Trajectory Computation Infrastructure A Predicted Trajectory Ground - based Automation System Flight Intent Controller Intent Generation Infrastructure G Aircraft Intent Initial State (surveillance) Trajectory Computation Infrastructure G Predicted Trajectory Ground-based Trajectory Prediction Figure 5 Possible types of information that can be shared to achieve trajectory synchronization Once the trajectory predictions are synchronized, and it is ensured that all involved systems use a coherent description of the flight to be managed, further negotiation processes are possible when the actual trajectory does not comply with the ATC restrictions or even more, when some user preferences are not met. Although both situations are totally different, the first implies safety issues, whilst the second only affects to the airline commercial strategy, the negotiation process can be described exactly in the same way. The NextGen Avionics Roadmap [10] establishes in the TBO Framework Appendix four phases for describing this process: - Pre-negotiation. The initial user preferred trajectory is shared with the ANSPs. If some potential conflicts are foreseen, some ATC restrictions are violated or any capacity imbalance is detected, the negotiation process is launched, otherwise the trajectory is agreed by the operator and the ATM authorities. - Negotiation. For those trajectories that do not comply with the ATM requirements, the ground-based trajectory prediction infrastructure generates strategic or tactical amendments to the original trajectories depending on if the problematic situation is detected during the planning phase due potential conflicts with other SBT, or during the execution phase due to higher deviation from the nominal RBT. These amendments have to be issued considering safety at first, but also taking into account the user preferences if known. For the proper generation of such Author: Enrique Casado 17

23 corrections to the RBT, the automation tools must be synchronized with the information managed onboard 8 (or by the AOC during the planning phase 9 ) and have to be capable of generating alternative trajectories that can be executed by the considered aircraft under the specific weather and traffic conditions. After checking that the modified flight is free of conflicts and respects, as much as possible, the operator optimization criteria, the new RBT is uploaded to the aircraft (or shared with the AOC). After receiving this updated information, the user will rebuild the trajectory based on the transferred data and will check if this is compliance with their own objectives. If so, the negotiation process ends. Otherwise, the user can generate an alternative solution to be shared again with the ground systems in an iterative process. - Agreement. After solving any potential problem with the planned trajectory to be flown, and after ensuring that the proposed alternative is flyable and meet the most user preferences, the operator agrees on executing the negotiated trajectory and the ANSP agrees on not intervening except if safety is jeopardized. - Execution. The flight is executed in accordance with the agreed and cleared RBT. During this phase, the flight crew maintains the flight within certain defined performance boundaries and the ANSPs are monitoring the adherence actual trajectory to the RBT. 8 Air-ground synchronization. 9 Ground-ground synchronization. Author: Enrique Casado 18

24 4 TRAJECTORY PREDICTION Literature Review The list of automation tools that require trajectory information, especially trajectory predictions, for developing their own tasks in the current and also in the future ATM system is certainly wide, ranging from Flight Panning and Re-Planning, Flight Data Processing, Conflict Detection & Resolution, Sequencing & Merging tools or Traffic Flow Managers. In all cases, trajectory predictions are required to traffic flow optimization, strategic scheduling, sector loads forecast, correlation of actual and planned flight information, identification of medium and short-term breaches in the separation criteria, conflict resolution advisories design or estimations of the time of arrival at specific metering points. Due to the disparity of DSTs goals, the requirements over trajectory predictions are diverse in terms of accuracy, integrity and availability [21]. - Accuracy is defined as the difference between the actual aircraft trajectory and the prediction generated by the considered automated tool as a function of the look-ahead time. Such discrepancies are considered as prediction uncertainties that cannot be considered precisely by the TP when a prediction is computed. Commonly, the lateral and vertical uncertainties are considered separately because they are influenced by unrelated factors. Depending on the nature and goals of the specific DST, the required accuracy in both profiles can be different, and therefore, their evolutions with time can be managed independently. - Integrity represents the likelihood of providing misleading information to a DST without the appropriate alerting. The acceptable levels of integrity are directly related to the consequences on safety due to the undetected use of such erroneous data. According to this criteria, there are two integrity levels: nonessential for applications with less sensitivity to undetected erroneous inputs, such as traffic load managers; and essential for applications which cannot tolerate unknown erroneous information due to its relevant safety impact in the traffic operations, such as arrival managers. - Availability refers to the percentage of time during which the prediction is available for providing acceptable quality information to the specified DST. The most common factor which affects the availability is the rapid changes in the environmental conditions. When the wind conditions are relatively stable, the weather forecasts for the next hour or couple of hours are reasonably reliable. However, sometimes these conditions are not maintained reducing or even more eliminating the forecast usability provoking a loss of information availability. Although these high level requirements can be considered as measurements and comparisons applied to the TP outputs, it is obvious that TP performances are soundly influenced by the quality of the inputs and the theoretical modeling applied for their implementations. Thus, the IOOI (input, output, outcome, impact) [22] appears as an appropriate methodology for being applied to measure the TP performances, and therefore, to evaluate its suitability for providing prediction services to other DSTs. This framework is used for determining metrics that can describe the performances of any TP. A general overview would include: - Input Metrics try to describe the quality of the inputs required for the prediction process. The list of inputs, could present differences among TPs depending on the theoretical approach followed for their implementations. Basic metrics for evaluating the accuracy of input data could be: vector wind errors; initial position errors; intended speed errors; lateral route errors; or initial weight errors. Each of them has different influence in the trajectory prediction process ranging from along-track deviations with altitude errors during climb and descent; fuel consumption errors; or timing deviations. - Output Metrics represent the difference between the predicted trajectory and the actual trajectory executed along the flight. Most common metrics are defined at specific events such as the Top of Climb (TOC) or Top or Descent (TOD) or at metering points. Examples of metrics could be: time errors; altitude errors; along-track errors; or crosstrack errors. In all cases, the metrics measure the discrepancy between the predicted time, altitude and horizontal positioning and the real values. Author: Enrique Casado 19

25 - Outcome Metrics are designed for combining information of input and output metrics to provide wider performance indicators. Since the output of a TP is fully dependant on inputs, the method for analyzing the TP performance has to consider validated reference data to be used as input. This alternative eliminates the errors due to erroneous inputs and allows evaluating the performances based exclusively on the obtained outputs. These metrics are simply derived output metrics obtained when a fully known and controlled set of inputs is used for predicting a trajectory. - Impact Metrics refer to the effect of the TP performances on the client DST performances. When an automation tool is subject to minimum performance requirements, it is necessary to analyze how the features of the integrated TPs influence the global outcome. This characterization of the impact will allow determining the most effective TP improvements that really implies improvements in the throughput of client applications. However, the problem of defining a comprehensive set of TP metrics for examining the performances of one specific development is not closed yet. The first step towards such commonality was made by the FAA/Eurocontrol Action Plan 16 which aimed at defining a common methodology for validating TP capabilities [23]. The output was a nine-point action plan described by the following topics: - Common TP-related terminology to avoid misunderstandings due to the use of different terms with the same meaning for theoretical problem definition. - TP requirements survey to document the predictions needs of future advanced support tools and to adequate the TP performances to those required by the DSTs. - Proposed requirements for encoding of LOA/SOP 10 -defined ATC constraints to harmonize the description of those constraints and to allow their used automatically by any TP avoiding the need of manual customization of the applications that make use of them. - Comprehensive sensitivity analysis of TP factors to have a common framework for evaluation the TP performances and the quality of the generated predictions in accordance with the expected requirements of the client tools. - Performance-modeling evaluation to provide the means for the analytical assessment of the different techniques applied for aircraft performance modeling. - Requirements for aircraft performance data to provide standard information about a broad range of aircraft to be used as input of the performance models implemented by each solution. - Comprehensive TP validation reference data set to be used to categorize the prediction capabilities provided by each TP in a formal manner. - Assessment of the operational application of ATM constraints to analyze statistically the type and frequency of applied constraints such as published crossing restrictions or ATCO directives, and to organize a statistically significant sampling of typical airspace regions. - Comprehensive operational assessment of intent prediction errors to evaluate the events that produce the main error and discrepancies between the predicted intent and the finally executed intent. Due to the expressed need for developments harmonization, the AP16 provided a common vision of any TP architecture consistent with most of the current developments [24]. Figure 6 depicts the different processes and services that characterize a trajectory prediction functionality on which the DSTs might support their own capabilities. 10 Letter of Agreement/Standard Operation Procedures Author: Enrique Casado 20

26 Figure 6 AP16 Common Trajectory Predictor Architecture The four main processes [25] that govern any trajectory prediction as described in the common generalized architecture are: - Preparation process. It is the initial step which is triggered by the requirement of a predicted aircraft trajectory under certain conditions. The input data range from flight plan information, ATC constraints, ATM procedures or weather forecasts. From the initial inputs, the route information is translated into latitude and longitude points (Route Conversion). This list of points defines the lateral path to be flown by the aircraft (Lateral Path Initialization) and allow allocating the speed, altitude and time constraints to be fulfilled along the flight (Constraint Specification). Finally, the intent or description of how to operate the aircraft to perform the envisioned trajectory compliance with all ATC constraints is described based on the available information (Intent Modeling). - Trajectory prediction process. This process represents the kernel functionality of a TP. Using the information gathered by the Preparation Process and encapsulated in the Flight Script (FS), the Trajectory Engine (TE) integrates the system of equations of the implemented Aircraft Motion Model (AMM). The TE may have access to meteorological and aircraft performance databases for accurate and up to date trajectory computations. - Trajectory update process. Once a flight related information is updated due to the release of new constraints or a modification of the intent, the process of re-computing the prediction is launched. The recalculation monitoring is the responsible service of triggering the update process when a tolerance is exceeded or when the considered valid time interval is finished. This process can imply the generation of a new complete set of inputs or just a minor modification of the former ones (Information Updating Service). In both cases, the entire prediction process requires to be rebooted with the updated information. - TP export process. After a new trajectory prediction, the last stage is to share the output with any client application (Formatting Service). Additional features of this process would be the capability of monitoring the computation Author: Enrique Casado 21

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