AGIS: Integrated GIS Application for Air Traffic Control Support


Abstract

In the past, Geographic Information Systems (GIS) have been extensively applied to the management of various forms of ground based transportation, such as highway and rail. No large-scale applications of GIS technology have been applied to the management of civil and military aviation. This paper will discuss a GIS application that provides data and support to the Canadian Automated Air Traffic System (CAATS) currently under development by Hughes Aircraft of Canada. It will discuss the unique spatial problems involved in the world of aviation, focussing on the issues raised in the design of Air Traffic Control (ATC) systems. It describes how these problems are solved using an integrated application developed with the ArcInfo GIS, the Oracle Relational Database Management System (RDBMS) and a collection of utilities developed in Ada.


Contents


1.0 Introduction

CAATS is a computer based system which automatically acquires, processes, distributes and displays flight data and related aeronautical information concerning aircraft which are under the jurisdiction of an air traffic controller. The CAATS provides:

  1. Automated real-time flight data processing and position updates for radar and non-radar trajectories.

  2. Conflict free flight profiles for all Instrument Flight Rules (IFR) and Controlled Visual Flight Rules (CVFR) aircraft outside radar coverage areas.

  3. The capability of detecting and predicting traffic conflicts.

  4. A weather model for accurate calculation of flight times and minimum time tracks.

  5. The capability to gather, store, analyze and transfer statistical data on air traffic operations and movements.

  6. The capability to record and playback flight data for accident/incident investigation and operation staff training.

  7. The capability to provide operational training at the regional Air Traffic Services (ATS) training units.

The core of CAATS is the Distributed Virtual Machine (DVM). The DVM represents a portable suite of integrated services, developed in Ada, for building a variety of distributed fault tolerant applications [1]. Constructed on top of the DVM is a collection of ATC application software. These applications include airspace and flight management, recording and playback, and ATC simulation.

One of the primary tasks of the DVM is to distribute static and dynamic information to client applications. Dynamic information represents real time data fed into CAATS, such as the state of flights as they track through a controller's jurisdiction. Static information represents data, which changes infrequently, such as the location and properties of a NAVAID or the segments and attributes of an airway. The system being introduced in this paper is concerned with the modeling and preparation of the static information for an operational ATC. The off-line data management portion[1] of CAATS consists of a collection of software and activities designed to feed the on-line portion[2] with static data. Diagram 1 shows the high level architecture of CAATS which puts the DVM, its operational clients, and its off-line database in context.

The off-line database contains two classifications of data, and two distinct types of databases. The resource database consists of information, which configures the components of CAATS. Examples are the configuration of a physical or logical network, the setup of controller workstations, or messages presented to a controller. The adaptation database consists of information, which is fed to the on-line system to populate objects, which are then used during the operation of the ATC system. Examples are NAVAIDS, aerodromes and airways.

The two databases supporting CAATS are a spatial database (ArcInfo) and a tabular database (Oracle). This paper will discuss the spatial component and its use of GIS technology.

The purpose of the Aeronautical Geographic Information System (AGIS) is to:

  1. Load data into the Spatial Adaptation Database (SADB) from sources external and internal to CAATS.

  2. Build maps from the SADB, and compile these maps into a format suitable for display and manipulation on a controller Situational Display.

  3. Maintain and validate the geometric component of airspaces.

  4. Distribute subsets of the SADB to the various sites within CAATS.

2.0 Creation and Distribution of the National Database

The first step for the AGIS is to define and populate the SADB for use at the various sites of CAATS. The use of this national database insures data consistency across all CAATS sites, which are widely distributed across Canada. The major sites of CAATS are:

Diagram 2 illustrates the structure and flow of data throughout CAATS.

2.1 Major Classes of Data

The classes of data contained in the SADB are classified as aeronautical or non-aeroautical. Aeronautical classes are of interest to ATC. A subset of these aeronautical classes is:

FIX: Consist of any geographic location or navigation device, which is used by an IFR or CFVR flight in maintaining their filed flight plans. A fix may be an intersection, a geographic location or one of a collection of NAVAIDS.

AERODROME: Consists of any site where a plane may land or take off. This may be as large as a major international airport or as small as a grass strip on the outskirts of a small town.

AIRWAY: Consist of an ordered sequence of FIXES, which define a published path. Airways are analogous to a shipping lane with the addition of altitude. IFR flights file flight plans against airways or portions of airways.

AIRSPACE: An airspace consists of a volume of the atmosphere. Its purpose may be to mark the vertical and horizontal boundary of a jurisdiction, a physical phenomenon or the existence of an activity of interest to a flight.

With the exception of airspaces[3], all aeronautical data are loaded into the SADB from within CAATS, via Oracle into ArcInfo. External data in the form of internationally and nationally published data sets are ingested by the Tabular Data Management Subsystem (TADM). They are parsed, validated and stored into Oracle tables. Views are presented to AGIS, which converts the tabular representation into coverage models, complete with classification, attributes, and symbology.

Non-aeronautical data is used primarily for context and reference on maps and during the creation of airspaces. A subset of this data supported on CAATS is:

Geographic information is provided by external sources in a format that can be directly loaded into a coverage model.

2.2 Spherical and Planar Considerations

In general the products maintained by AGIS are large area and small scale. The extent of many of the objects is large enough that the effect of approximation on a plane can introduce large errors.

Many GIS applications use local approximations to the earth by projecting geodetic coordinates onto a plane. Errors in position introduced by the planar model are small because the objects under consideration are small or the data is dense. This is not always the case in ATC where the data is sparse and, the spatial extent is large. Errors are deceptive and can imply an unsafe course of action

In AGIS the following geometric primitives are used to describe complex objects:

The problem for ATC comes down to the density of the sampled data. The best course here is to discuss the problem in parallel with an example. An airway segment is represented by a great circle between two fixes. If we project the fixes onto a plane, and then describe the airway by connecting the two points, a substantial error is introduced. In reality, a flight tracking along this airway will sweep out a curve, as shown in diagram 3. The maximum error will occur at the midpoint. This error is largest when the two points have the same latitude. If the latitude is 0, there is no error. As the latitude increases (or decreases), the error increases. Performing explicit over-sampling of the great circle will reduce the error. Each point introduced will decrease the error, which will never vanish, but can be minimized. It now becomes a balance between the issue of safety and the volume of data used to model a phenomenon.

The solution to this problem of geodesy is to reuse components of the on-line ATC. CAATS supports a collection of tools for performing geometric operations on a sphere. The tools are used in a myriad of tasks, such as calculation of the predicted and actual time of flight intersection with airspaces. An interface was developed which allows the AGIS application to call, directly from ARC Macro Language (AML), a subset of the Geometric Services (GEOM) subsystem. The services provided include great circle segment intersection, and small and great circle segment densification. This interface is used extensively throughout the subsystem, initially when data is ingested into the system, but also in the interactive construction of airspaces.

2.3 Managing Classes of Data

The AGIS subsystem was developed to accept data in a generic fashion from external and internal sources. When a new class is introduced, minimal or no change to software is required. AGIS has a generic method for describing the spatial and tabular structure of a class of data through its resource database. The class is mapped to one of a collection of supported spatial classes which includes line, polygon, region and route. A template defines the attributes of the class. Together this forms the model of the class. A combination of generic software and standardized views allows for the population of coverages with data for a class that is independent of the spatial and tabular data format.

3.0 Creation, and Compilation of Controller Maps

As with many GIS applications, one of the primary tasks of the AGIS is the creation, and customization of maps. For CAATS, the primary mapping requirement is for the generation of controller maps. These maps are created off-line by AGIS, and compiled into a format, which can be displayed on a controller's Situational Display (SIT). The SIT is a graphical display covering the airspace under the controller's jurisdiction. Contained on the display are mixed overlays of static and dynamic data.

3.1 Composing and De-Cluttering a Map

Maps are generally developed to cover sectors. Sectors represent an airspace that a controller will manage. The scale of maps can be widely varying, covering an area from 250 to 10,000 square nautical miles. The level of detail can range from sparse for an operational map, to dense for a training map.

Maps are composed in three phases: preliminary, composition, and de-cluttering. In the preliminary phase, the high level components of the map are specified. This includes the label, the spatial extent of the map, the map projection, the magnetic declination at the map center, and a time period under which the map is considered valid. In the composition phase, the levels of the map and the classes of objects contained in the levels are defined. Levels are generally thematic, containing all objects of a certain class, such as all airways, or a specific type of aerodrome. The display order of levels can be manipulated. In the de-cluttering phase, the objects in the map are tailored to a specific need. This operation centers on removing subsets of data, either by exclusion of individual objects or the clipping out of collections of objects. Tailoring of annotation is supported in the form of exclusion or displacement. An example of a map developed by AGIS is shown in diagram 4.

3.2 The Copy and Recreate Operation

The composition of maps is a labour intensive task. Upward of 100 maps may be required at a single ACC, with additional maps required for Tower Control Centers (TCC). Further, the SADB changes over time, as new data sets are ingested, and the addition and removal of information alter existing data sets. Rather than requiring the user to sift through the SADB for changes, a Copy and a Recreate operation are defined on maps. The Recreate operation will automatically refresh components of a map to be in sync with the SADB. The recreation operation can be performed incrementally on components of the map, or the entire map can be regenerated from scratch. During initial map composition stage, all operations performed on the map are recorded. On the request for recreation, specified components of the map are regenerated from the stored operations set against the current version of the SADB. The recreation operation is designed to report, but not fail, in the event of a missing data class or object. This allows for maps to be regenerated against vastly different versions of the SADB without problems. The copy operation allows for one map to be automatically copied into a new map, and generated against data in the current version of the SADB. The destination map initially inherits the preliminary components of the source map. However, this information can be changed prior to the actual generation of the level and class data. The most common components changed are the spatial extent and the projection. The copy operation is based upon the recreate operation and so, has the property of not failing if a class or object does not exist in the SADB. The map developer may then create a template with preliminary and composition components defined. This template may then be copied to different spatial extents and projections, automatically inheriting the level and class structure of the template map.

To support composition, recreation, and copying the map exists in two structures. The explicit and implicit map co-exists as a parallel database. The implicit map is modeled and supported in Oracle. The explicit map is modeled and supported in ArcInfo. During the initial composition of the map, all instructions are recorded in the implicit map and concurrently elaborated in the explicit map. The implicit map exists as a collection of inter-related rows in a collection of Oracle tables, while the explicit map exists as a displayable entity. The copy and recreate operations require only the implicit map and the SADB to exist. From this representation the explicit map can be derived, either in its original form through the recreate operation, or as a new map through the copy operation.

3.3 Compilation and Distribution of Controller Maps

When the development of a map is complete it is compiled and shipped to the on-line world for use by controllers. When a map has reached a state where it meets the needs of a given controller, it is compiled. Compilation transforms the implicit and explicit model of the map into a format, which is directly displayable on the SIT. The destination format is InterMaphics Data Definition Language (DDL), which is the Commercial-Off-The-Shelf (COTS) product that drives the SIT display. The compilation stage will translate the structure of the implicit map and the geometry and display characteristics of the explicit map into DDL.

Subsets of aeronautical classes support pick operation on the SIT. The pick operation allows a controller to select the object on the SIT and get additional information on it. During compilation, the pick key is embedded with the spatial information. Software in the on-line world traps this embedded key at pick time, and queries the real time database of the DVM for the most current data associated with this object. For example, a NAVIAD has a schedule of operations, a frequency, and may be shut down temporarily for repairs. When a pick is performed on a NAVAID, the current version of this data may then be presented to the controller.

The map is distributed in two components. The first component is the DDL file. The second component is the preliminary information on the map, which is not captured in the graphics. This information is extracted from AGIS and processed into a Fast Load File (FLF) by TADM. A FLF is the binary image of an Ada object captured as a byte-stream. The FLF is the primary method by which data from the off-line system is distributed to the on-line system. TADM extracts information from the database and calls a client constructor, which returns an Ada object. The object is encoded into a FLF. This FLF is then injected into the DVM, which looks after transmission and delivery of the FLF to the on-line client. The SIT clients receive notifications from the DVM that a set of FLF representing maps is available. The client then retrieves the graphic portion of the map on demand. The DDL portion of the map is not distributed via the FLF method. This is primarily because of the volume of data in this representation. A different mechanism of the DVM looks after synchronizing the DDL and the FLF and distributing it to the on-line world.

3.4 Consistency between the Off-Line and On-Line Map

A map developed by AGIS must be identical to the map presented to a controller. During the compilation process, the resource database is queried for the off-line to on-line mapping of the respective representations of symbols, line styles, annotation and colour. For each class of data, the ArcInfo display properties are mapped to the InterMaphics display properties. Initially when the SADB is populated, the ArcInfo display properties are assigned. On compilation of a map, the InterMaphics representation is determined with its symbolization extracted from the resource database. This process allows for the two display environments to always be synchronized. The resource database also models the on-line picking key. For each class of data that supports the pick option, a collection of attributes describing the pick key is maintained. When the SADB is populated, this structure is created on the class in the coverage model, and populated with the correct attribute values. Upon compilation, this information is then extracted and placed into the embedded key.

4.0 Creation, and Compilation of Air Spaces

The aeronautical world exists in the atmosphere and only briefly touches the planet to refuel and reload. The real action is in the sky. As the number of flights, be they commercial, private or military increases, the skies have become increasingly dense with traffic. This puts a premium on managing the airspace that these flights must pass through.

4.1 The Use and Meaning of Airspaces

An airspace spatially consists of a volume of the atmosphere. They are defined horizontally by a closed loop of great circle and small circle segments, and vertically by an upper and lower altitude. The attributes associated with the underlying volume describe the purpose of the airspace:

  1. Identify jurisdiction, from a small control area around an aerodrome to domestic airspace;
  2. Identify a physical geographic phenomenon, such as areas of compass reliability;
  3. Indicate the availability of radar coverage;
  4. Indicate an activity, which flights in the area must be cognizant of such as blasting, weapons testing or parachuting;
  5. Load balancing for controllers.

With a well-defined spatial model for an airspace, real time spatial relationships, such as containment and intersection may be determined between actual and predicted flights. The properties of these relationships can then be associated with a flight at a particular instant in time. The AGIS manages with four kinds of airspaces:

Static Airspaces: Static Airspaces represent airspaces that are essentially unchanged over time. In general static airspaces are published internationally. Examples are Flight Information Regions, Domestic Airspace and Compass Unreliability Regions.

Special Use Airspaces: Special Use Airspaces (SUA) represent airspaces where restrictions to normal flying are under effect. These restrictions may or may not be scheduled. For example an Alert Area is an airspace where a high volume of pilot training, or unusual aerial activity such as parachuting occurs.

Sectorization Plans: A sectorization plan is used for managing the airspace from an ACC perspective. Each sector represents a subset of the airspace that a controller will manage. Sectors are composed of sub-sectors that can be rearranged to react to changes in the load of traffic.

Radar Coverage: A radar coverage airspace represents the volume of airspace that can be seen by a radar installation. Over a given area, multiple radar sites will provide primary and secondary coverage for aeronautical facilities. Modeling this radar coverage as an airspace allows for the system to adapt to the failure of a radar site.

4.2 GIS Modeling of Airspaces

The off-line world models the various types of airspaces, and transforms them into representations, which the on-line world can use. AGIS models the geometry, and TADM models the attributes.

Airspaces are introduced to the system from an external source in three components: static attributes, vertical geometry and horizontal geometry. TADM ingests the external airspace definitions into tables, validating content and insuring consistency with the on-line representation of airspaces. The horizontal and vertical components are then converted by AGIS into airspace coverage models.

Airspaces are modeled spatially by the simple volume model. A simple volume consists of a closed polygon on the sphere, and an associated altitude interval. Sets of simple volumes are grouped into complex volumes. Collections of volumes model airspaces, and are separated into two classes: partitioned and non-partitioned collections. In a partitioned collection, the spatial relationships between each simple volume are known, and a strict set of geometric rules is applied. In a non-partitioned collection, each volume is essentially stand-alone, and no rules are applied to the collection as a whole, only to the individual volumes.

An application of the region model in ArcInfo and a collection of AML developed algorithms support the creation of volume collections. The following rules are applied to all collections:

  1. Polygonal Rule: Every simple volume must have a representation on the sphere that is a simple, connected polygon.

  2. Vertical Rule: The vertical interval, which the polygon is defined over, must consist of two altitudes with the lower altitude less than the upper altitude.

    If the collection falls under the non-partitioned class, no further rules apply. If the collection falls under the partitioned class then the following additional rules are enforced:

  3. Simple Volume Overlaps: No two simple volumes can share the same airspace vertically or horizontally.

  4. Simple Volume Holes: Simple volumes must fill the entire airspace being partitioned. This applies both vertically and horizontally.

  5. Complex volume Overlaps: No two complex volumes can share the same simple volume.

  6. Complex Volume Union: Every simple volume must include at least one complex volume.

  7. Connectivity: Every complex volume must consist of a set of face connected volumes. Edge and vertex connectivity is not acceptable. All volumes are connected if spheres of infinitesimal radius r, contained in each respective volume, have a cylindrical path of radius r exists between the spheres which does not exit the partition.

Given the definition of partitioned and non-partitioned collections, airspaces map into the classes as follows:


Examples of volumes and collections are shown in diagram 5.

A general-purpose airspace editor is currently under development. This tool will allow for a user to interactively define both partitioned and non-partitioned volume collections, verify the rules applied against them, and suggest a course of action for correcting any problems. In addition, display tools have been developed to aid in visualizing the three-dimensional properties of the airspace using its two-dimensional planar representation.

4.4 Compilation and Distribution of Airspace Models

Once a volume collection has been validated, it is then compiled and distributed to the operational ATC. A grammar was developed by GEOM for modeling volume collection on the sphere. AGIS converts from the off-line planar model into the on-line spherical model. The compilation steps are different for each class of airspace.

Non-Partitioned Airspaces: The geometry of each individual volume is extracted from the coverage model, converted to its spherical grammar representation and added to the GEOM model of the volume collection. No relationships between the volumes are determined.

Radar Coverage Airspaces: The geometry and availability of radar coverage both horizontally and vertically are captured into a grid. Each grid cell represents a patch on the sphere which contains an ordered list of radar sites and altitudes which the radar has a line of sight.

Partitioned Airspaces: This is the most complex volume collection AGIS must deal with. It uses the same grammar as the non-partitioned volume collections, with the additional complication of requiring that all geometrical relationships between the volumes in the collection be determined. This cascades from the low-level relationships between points, curves, and altitudes, up to the more complex arena of open and closed surfaces, volumes, and finally unions of volumes. In addition, the orientation of all objects must be determined, and the construction of geometric primitives such as vertical faces must be minimized.

The output grammar is inserted into what is called a "Black Box" table in the TADM database. This information is extracted as an anonymous stream of data by TADM and encoded into a FLF, which is then distributed to the on-line world through the DVM. The "Black Box" methodology is employed for consistency and minimization of validation. The TADM subsystem is responsible for the creation of all FLF for CAATS. Rather than having AGIS, which is primarily concerned with geometry, deal with FLF creation, TADM applies its well-developed process and software to creating the FLF. The anonymous or "Black Box" approach was used to minimize the repetition of validation. The coverage model and its suite of supporting software perform all verification and validation of the airspace geometry. There is no need for TADM to perform any more consistency checking on the geometry. It is only required to construct the operational model from the contents of the anonymous column, and link the geometry and the tabular attributes together in the Ada object, and ultimately the FLF.

5.0 Conclusion

The realization of AGIS demonstrates again the power and diversity of the GIS. This represents an application of a GIS in support of a fault tolerant, safety critical system. Over the course of design and implementation, care has been taken to insure that AGIS consists of a flexible and consistent suite of models and software for supporting the ATC system. It is designed to be extensible, and to accommodate changes to on-line representations of data with minimal changes to its software.

GIS has probed the oceans, the earth's core and surface. It can now be said that GIS has finally left the ground for the atmosphere. The next step can only be upward and beyond to space. The author hopes to see the development of the first Cosmological Information System in his lifetime.


Bibliography

  1. Thompson, Christopher J. & Celier, Vincent, "DVM: An Object-Oriented Framework for Building Large Distributed Systems," Proceedings of TRI-Ada '94 Conference, Anaheim, California

  2. Designated Airspace Handbook, Published Under the Authority of the Minister of Transportation, Transport Canada, 28th of April, 1994

  3. Garrison, Paul, How the Air Traffic Control System Works, TAB Books, 1979

  4. Instrument Procedures Manual, Minister of Supply and Services, Canada, 1987

  5. Aranoff, Stan, "Geographic Information Systems: A Management Perspective", WDL Publications, 1989

  6. Laurini, Robert and Thompson, Derek, "Fundamentals of Spatial Information Systems", ACADEMIC PRESS LTD, 1994.


Footnotes

[1] Not a component of the operational ATC system, and concerned primarily with the consistency and correctness of static ATC and configuration data.

[2] The operational ATC system, real time and fault tolerant, concerned with the real time management of air traffic.

[3] The ingesting of airspace data is discussed in section 5.0

[4] For the purposes of clarity of discussion the earth is assumed to be a perfect sphere.

[5] With the exception of the equator, which is a great circle

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