This paper describes design and implementation details and pertinent results from a recently delivered research project, Trajectory Based Operations (TBO)/Unmanned Aircraft Systems (UAS) that was led by Boeing Airspace and Operations Efficiency (AOE). TBO/UAS project's main purpose was to demonstrate and analyze the trajectory negotiation operational procedures and concepts involved in management and deconfliction of aircraft in the cruise phase of flight in Class A airspace. The research and development (R&D) activities represented in this project potentially apply to both manned and unmanned aircraft systems operations. The operational system environment was that of the expected air traffic management (ATM) system capabilities in the future; this was defined to include a Four Dimensional Trajectory Based Operations (4DTBO) system with negotiated trajectories supported by System Wide Information Management (SWIM). The outcome of the research was that a basic form of TBO could be implemented now with standard commercial avionics and Flight Management Computers (FMC) in the aircraft and current communications protocols, leading to significant fuel savings, but ANSP systems development would be required. With ground system decision support tools supporting 4DTBO in place, transition to full 4DTBO would be a matter of the aircraft upgrading their systems.

This paper describes a series of short experiments collecting and analyzing ADS B data using IoT (Internet of Things) devices. The collection is performed using a Raspberry Pi single board computer, an RTL-SDR radio, custom software written for the project, and the open source dump1090 software program. This Raspberry Pi/RTL-SDR/dump1090 combination is used to collect ADS-B data. The data is captured and archived using a software program that reads the ADS-B data in real time as it is received by the RTL-SDR radio and subsequently output by the dump1090 program. The captured data is written to a series of flat files. Subsequent analytics and analysis is performed using the R programming language and the R Studio environment. The paper describes a subset of the R code that that was used in the analysis. All of the custom software used in this project is freely available at GitHub (see References section).An exhaustive analysis is not performed as part of this work. The intent of the limited analysis in this work is to provide a proof of concept for the kinds of analyses that could be done, if aviation data, such as ADS, was widely and freely available.The analysis that is performed is an initial top level analysis, designed to assess the feasibility of using this low cost combination of hardware, software, and analysis tools for use in advisory air traffic applications such as airspace monitoring and traffic monitoring. Suggestions and recommendations for additional work appear in the Observations and Continuing Work sections of this paper.

About Federated Identity Management (FIM) • FIM — provides cross-organizational, role-based access controls — transformation of local user credentials into standards-based security token that a remote system can trust • Exchange some token to establish user identity on a remote system — Can use attributes in token to determine user roles and privileges • How can identity federation be useful? — Don't have to replicate or synchronize local user repositories — Users need to remember/maintain fewer logon credentials — Dynamic access improves efficiency and security • 2 Parts — Business agreement and technical implementation — Federated identity ensures that a user's or system's trusted identity provides a secure means of identifying all entities across systems and enterprises regardless of where the data flows. It also provides and audit trail on what people and systems accessed the data.

This paper describes various approaches to secure interagency information sharing. The common objective of these approaches is to use federated credentialing as the basis for controlled access to federated, multi-agency information. The exemplary scenario for federated information sharing consists of FAA flight information being shared with authorized persons or organizations within a partner agency, such as the Department of Defense (DoD) and the converse. Approaches we explored involve an identity provider (IdP) entity that authenticates a user/client and provides a security token for consumption by a service provider (SP) entity accessed by the client. Since the emulated agencies maintain distinct security domains, secure information-sharing approaches involve varying combinations of IdP and SP entities spanning the emulated interagency boundary.

The purpose of this work is to promote and advance interoperability between aviation information systems. Modern information systems require a flexible, scalable, and upgradeable infrastructure that allows communication, and collaboration, between heterogeneous information processing and computing environments. Aviation systems from different organizations often use differing representations and distribution policies for the same data and messages, limiting interoperability and collaboration. Although this problem is conceptually straightforward, information exchange is error prone, often dramatically underestimated, and unexpectedly complex. In the air traffic domain, complexity is often the result of the many different uncorrelated information processing environments that are used. The complexity and variation in information processing environments creates a barrier between domain practitioners and the engineers that build these systems. These divisions have contributed to documented systems failures such as the FAA's Advanced Automation System and the FBI's Virtual Case File. Operationally, difficulties in sharing information have contributed to significant coordination challenges between organizations. These coordination problems are evident in events such as the response to Hurricane Katrina, the Minneapolis over flight of October 2009, and other incidents requiring coordination between multiple organizations. To address interoperability in the aviation domain, a prototype Domain Specific Language (DSL) for aviation data will be designed and implemented. The DSL provides the capability to specify and create aviation data for use in the aviation domain. The DSL is designed to allow the domain practitioner to participate in dynamic information exchange without being burdened by the complexities of information technology and organizational policy. The DSL provides the capability to specify and generate information system usable representations of aviation data. The DSL makes use of an aviation metadata repository that contains the representational details of the aviation data. The combination of DSL, aviation metadata repository, and data generation provide the capability for aviation systems to interoperate, enabling collaboration, information sharing, and coordination.

In this paper, we describe a novel analytics system that enables query processing and predictive analytics over streams of big aviation data. As part of an Internal Research and Development project, Boeing Research and Technology (BR&T) Advanced Air Traffic Management (AATM) built a system that makes predictions based upon descriptive patterns of massive aviation data. Boeing AATM has been receiving live Aircraft Situation Display to Industry (ASDI) data and archiving it for over two years. At the present time, there is not an easy mechanism to perform analytics on the data. The incoming ASDI data is large, compressed, and requires correlation with other flight data before it can be analyzed. The service exposes this data once it has been uncompressed, correlated, and stored in a data warehouse for further analysis using a variety of descriptive, predictive, and possibly prescriptive analytics tools. The service is being built partially in response to requests from Boeing Commercial Aviation (BCA) for analysis of capacity and flow in the US National Airspace System (NAS). The service utilizes a custom tool developed by Embry Riddle Aeronautical University (ERAU) that correlates the raw ASDI feed, IBM Warehouse with DB2 for data management, WebSphere Message Broker for real-time message brokering, SPSS Modeler for statistical analysis, and Cognos BI for front-end business intelligence (BI) visualization tools. This paper describes a scalable service architecture, implementation and value it adds to the aviation domain.

The maintenance of airport acceptance rates for arrivals and departures is critical to the performance of the National Airspace System (NAS). This paper develops a novel automated decision support system, named ADTOS, intended to assist traffic flow management specialists select the most optimal arrival and departure strategies. We have built and maintained a data warehouse using streams of aviation data as part of an internal research and development project at Boeing Advanced Air Traffic Management in Chantilly, VA. ADTOS leverages this data warehouse, making use of Aircraft Situation Display to Industry (ASDI) surveillance, Meteorological Aerodrome Reports (METAR), Terminal Aerodrome Forecast (TAF) data, and runway configurations. The warehouse database architecture and the arrival/departure tradeoff optimization module is presented with a validation case study in which ADTOS is utilized for strategic planning of arrival and departure traffic and airport capacity from 1 hour to 24 hours into the future at Dulles International Airport (IAD). The experiments demonstrate ADTOS' capability for rapidly processing large amounts of streaming aviation data and effectiveness over the existing traffic flow management by increasing airport throughput and reducing traffic delays during the time period of interest. The paper also presents initial results of the case study.

A collection of slides from the authors conference presentation is given covering the following topics: aviation; information sharing; and data models.

In this paper, we describe a novel analytics system that enables query processing and predictive analytics over streams of aviation data. As part of an Internal Research and Development project, Boeing Research and Technology (BR&T) Advanced Air Traffic Management (AATM) built a system that makes predictions based upon descriptive patterns of archived aviation data. Boeing AATM has been receiving live Aircraft Situation Display to Industry (ASDI) data and archiving it for over two years. At the present time, there is not an easy mechanism to perform analytics on the data. The incoming ASDI data is large, compressed, and requires correlation with other flight data before it can be analyzed. The service exposes this data once it has been uncompressed, correlated, and stored in a data warehouse for further analysis using a variety of descriptive, predictive, and possibly prescriptive analytics tools. The service is being built partially in response to requests from Boeing Commercial Aviation (BCA) for analysis of capacity and flow in the US National Airspace System (NAS). The service utilizes a custom tool for correlating the raw ASDI feed, IBM Warehouse with DB2 for data management, WebSphere Message Broker for real-time message brokering, SPSS Modeler for statistical analysis, and Cognos BI for front-end business intelligence (BI) visualization. This paper describes a scalable service architecture, implementation and the value it adds to the aviation domain.

This paper describes Internal Research and Development (IR&D) work in progress that is being performed by Boeing Advanced Air Traffic Management (AATM) and IBM. Boeing and IBM are implementing a service that records, retrieves, analyzes and visualizes patterns using aviation data. The initial implementation is based on aircraft surveillance data. Boeing AATM has been receiving live Aircraft Situation Display to Industry (ASDI) data and archiving it for over two years. At the present time, there is not an easy mechanism to perform analytics on the data. The incoming data is large, compressed, and requires correlation with other flight data before it can be analyzed. The service exposes this data once it has been uncompressed, correlated, and stored in a database for further analysis using a variety of descriptive, predictive, and possibly prescriptive analytics tools. The service is being built partially in response to requests from Boeing Commercial Aviation for analysis of capacity and flow in the US National Airspace System. The service utilizes IBM Warehouse with DB2, WebSphere Message Broker, XML Shredding, and will be used with IBM analytics products. This paper describes the service implementation and the value it adds to the aviation domain.

Information sharing in the digital age is essential to providing a means to communicate faster and more efficiently. In aviation and air traffic management, communication is critical to daily operational coordination. At any given time there are multiple lines of communication that exist between pilots, air traffic controllers, airline operators, and other National Airspace System (NAS) users. In response to the growing need for better information sharing capabilities, the FAA has invested in a capability called System Wide Information Management (SWIM), a part of the Next Generation Air Transportation System (NextGen). The primary focus of SWIM is to provide the right information to people when they need it. The SWIM program has been developing and implementing an information sharing infrastructure to provide data services to both internal FAA and external stakeholders. The current SWIM schedule calls for a phased deployment known as segments that build upon previously introduced capabilities and technologies. The FAA is currently in the planning and prototyping phase of segment two. While SWIM is developing and deploying new infrastructure and capabilities, research and development programs are looking at future applications of SWIM and new capabilities that can potentially assist users with getting access to better data in a more reliable manner. One example of this research and development is the Network Enabled Operations (NEO) program, which demonstrated potential future uses of SWIM in assisting in airspace coordination and traffic flow utilizing the planned segment two infrastructure. The purpose of this paper is to outline in high-level summary the deployment strategy and status of SWIM segment two and to highlight the research and development work accomplished by NEO over the past year.

Presents a collection of slides from the author's conference presentation. The specific areas/topics discussed include: NEO (Network Enabled Operations) Background; Objectives; Applying NextGen Technologies; NEO Network Connectivity; Flight Test; and Lessons Learned and Observations.

This paper describes the work that was done by Boeing Advanced Air Traffic Management (AATM), Boeing Research & Technology Europe (BR&TE), Selex Sistemi Integrati, and Boeing Networked Systems Technology (NST) on the European Commission SWIM-SUIT Interoperability project. This work was sponsored by the European Commission and the US FAA. The goal of this project was the implementation and demonstration of SOA compliant mediation and distribution services for the exchange of live surveillance, flight plans, and flight objects between US and European aviation systems. The mediation service provided transformation between flight data defined by ASDI, ERAM and ICOG schemas. The Surveillance data was represented using FAA and Eurocontrol schemas. In addition to operational capabilities, this work featured the use of an improved distributed messaging technology developed by IBM known as Responsive, Reliable, Real-Time (R3) messaging. R3 messaging provides deterministic Quality of Service (QoS) overlays for use in a federated Enterprise Service Bus (ESB) environment. In addition to the R3 technology, the project featured the use of Mashups. Mashups provide the capability for a user to dynamically combine data and services in user specified configurations, resulting in user defined lightweight network-enabled applications. This paper shows how the mediation, distribution, and messaging services were implemented, example results, and how this work could be leveraged to facilitate US and European interoperability in the aviation domain.

The Network Enabled Operations (NEO) Spiral II Program is a collaborative effort that brings the FAA and a Boeing-led industry team of 14 partner companies and organizations together to explore concepts that will help to advance the operation of future unmanned aircraft system's (UAS's) integration in the National Airspace System (NAS): (1) Enhanced FAA intra-agency information sharing using capabilities in a distributed Service Oriented Architecture (SOA) based SWIM environment that can be extended to include other agency systems. (2) Enhanced collaboration and information flows via the sharing of aircraft intent using Aircraft Intent Description Language (AIDL) to enhance aircraft trajectory prediction (i.e., trajectory based operations) capabilities, including a broader sharing of four dimensional trajectories (4DTs) across ground automation systems. (3) The use of these tools in advancing the safety case for UAS operations in the NAS. (4) Dynamic airspace protection using Airspace Volumes of Interest (AVOIs). (5) Exploring enhanced net-centric procedures and information sharing approaches for UAS loss of control link eventualities.

This article consists of a collection of slides from the author's conference presentation.

This paper describes work that is being performed by Boeing Advanced Air Traffic Management (AATM) to provide initial interoperability between US and European aviation and air traffic control systems. Interoperability is demonstrated by using modern information technology tools and techniques to exchange information between the Boeing AATM test bed in the United States with the European Commission System Wide Information Management Supported by Innovative Technologies (SWIM-SUIT) network. Boeing Research and Technology Europe (BR&TE) in Madrid, Spain is a member of the SWIM-SUIT team. The Boeing AATM test bed in the US consists of nodes in Chantilly, Va., Kent, Washington, and Embry Riddle Aeronautical University in Daytona Beach, Florida. The SWIM-SUIT network has nodes in Madrid, Spain, Brussels, Belgium, Rome, Italy as well as other European cities. The gateway between the two networks is realized by connecting the Boeing facilities in Chantilly, Va., and Madrid, Spain. The Boeing AATM test bed has evolved from an early prototype of the FAA System Wide Information Management (SWIM) initiative. Test bed core services such as messaging, mediation, and user and identity management were used in the US governments multi-agency Joint Network Enabled Operations (NEO) program.

Presents a collection of slides that discusses the following; aviation data; domain specific languages; ultra-large scale systems; and data management.

This paper describes the work that was done by Boeing Advanced Air Traffic Management (AATM) and IBM on the Joint Network Enabled Operations (NEO) Spiral One Project and carried forward using internal research and development funding. NEO is a project that provides interagency communication and collaboration through the use of modern network focused information systems tools and technologies. The work described here provided a set of aviation related data and services that could be combined by using IBM's Mashup technology. Mashup technology provides the capability to create lightweight, network- enabled applications by combining data and services according to user specifications. The Mashup environment allows users to create these applications in minutes. The applications are created by combining data and services that are realized as reusable components called widgets. Using the IBM Mashup environment, widgets providing access to aviation specific data and services such as an airports database, a runways database, Notices to Airman (NOTAM), Meteorological Reports (METAR), NOAA Rapid Update Cycle (RUC) Weather, the Corridor Integrated Weather System (CIWS), and other geospatial services were created. This paper shows how these widgets can be “wired” together to address a variety of aviation specific business cases.

This paper describes internal research and development work that is being done by Boeing Advanced Air Traffic Management (AATM), Boeing Research & Technology Europe (BR&TE), and Boeing Networked Systems Technology (NST) on global Air Traffic Management (ATM) Interoperability The primary goal of this project is to provide a mediation service for flight objects Seamless exchange of both U.S. ERAM flight objects and Interoperability Consultancy Group (ICOG) flight objects can be achieved by utilizing a mediation service that employs an enterprise integration messaging pattern such as Java Messaging Service (JMS) publish/subscribe. A mediation service provides the transformation and mapping between flight objects defined by U.S. systems (i.e. ERAM) and ICOG compliant systems. Using U.S. and ICOG flight object schemas, elements are mapped supporting the most efficient method of content handling such that the payload for flight objects in one schema is preserved when translated to another. The transformation is performed on the fly using IBM's Message Broker technology. U.S. flight objects are translated into ICOG flight objects by the mediation service and delivered as ICOG flight objects and vice versa. IBM WebSphere Message Broker, IBM Harmony, and IBM rtJMS (Real-Time JMS) technologies are used for this effort. This paper shows how the mediation service is implemented and the value that it adds to global ATM interoperability.

This paper describes work that was done to explore and define mechanisms to realize these federated inter-agency trust relationships. An experiment was performed to provide a trust relationship between the DOD DIB (DCGS information backbone) and the FAA prototype demonstration core services for system wide information management. The trust relationship was mechanized using security assertion markup language (SAML) tokens as identification credentials.