Activity 11 - Airspace Concept Validation

This activity can be made up of several validation methods; the planning of which should begin in Activity 3 as validation platform availability can affect the project timescales.  Validation is the way of demonstrating that the project objectives as well as as safety and performance criteria can be achieved.  Iterations could be required between validation methods and, very exceptionally, with Activities 7 through to 9.

In general terms, Quantitative assessment refers to validation methods that are numerical.  A Qualitative assessment relies on the professional judgement of, normally, the personnel involved with that specific airspace.

In the main, validation is undertaken using elements of both qualitative and quantitative assessment.

There are several tools or methods available to undertake validation of the airspace concept, or the validation of specific procedures or to validate certain elements of the concept. These are:

  • Airspace Modelling
  • Fast-time Simulation (FTS)
  • Real-time Simulation (RTS)
  • Live ATC Trials
  • Full Flight Simulator
  • Data Analytical Tools
  • Statistical Analysis
  • Collision risk modelling (CRM)

Each of these tools differ in terms of cost, realism (and complexity), time and the number of traffic samples and test cases used.  Generally, the more complex the simulation method used, the greater the cost, preparation/run time required and the closer to reality the results become. In contrast, and normally for reasons related to cost/time – the number of traffic samples/test cases tend to decrease as the complexity of the simulation method used increases.

Airspace modelling is seldom used in isolation to validate an airspace design, but tends to be the first of several validation methods used. Like most validation tools, airspace modelling is computer based.

Generally, airspace modelling is used during the conceptial design phrase because it enables the airspace design team to visualise, in three dimensions, the placement and profile of routes, the airspace volumes and the sectorisation. This ability to see in three dimensions is extremely useful.

Airspace modelling tools can be considered as 'scaled down' version of Fast Time Simulators (FTS). Their main usage is to create a non-refined representation of the routes and airspace volumes (sectors) together and their interaction with a selected traffic sample. The tool generates simplified 4D trajectories (position + time) for the aircraft according to the flight plans described in the Traffic Sample (with its Rules) in a particular Airspace Organisation (with its Rules). This process is called traffic assignment. These trajectories are used together with the airspace blocks to calculate a series of statistical data such as: sector loading, route segment loading, conflicts, etc. Some more advanced airspace modelling tools can derive more precise data with regard to the workload and sector capacity.

As a validation methodology, Fast-Time simulation is a frequently used tool to validate a proposed design; it may also be used as a way of demonstrating that the safety objectives can be met.

In some cases, airspace design teams do not use airspace modelling and use fast-time simulation as the first step in the validation process. Usually used as a step to real-time simulation, FTS might also be the only step used to validate the concept. Because fast-time simulation is less demanding than real-time simulation in terms of human resources, this is often a preferred method for improving the proposed design, identifying flaws in the design concept, and/or preparing the path to real-time simulation or direct implementation.

Fast Time simulators need the airspace organisation and Traffic Sample to be defined for the simulated environment using specific computer language and the parameters that are needed include Routes, a traffic sample which is assigned on the routes, Airspace volumes and Sectors and Rules for aircraft behaviour.

The simulator engine generates 4D trajectories (position + time) for each aircraft based upon flight plan information and rules stated in the Test Cases. The system checks each trajectory for certain predefined events. Examples of such predefined events may include conflicts (remembering that defining the parameters of what constitutes a conflict might need to be written into the rules), level changes, routes changes, sector entry or exit. When such an event is detected, the system increments the defined counters and trigger tasks parameters linked to the event. For example, if the system detects that an aircraft has crossed a sector boundary, it will increase by one the number of aircraft counted in that specific sector and will trigger as active the tasks assigned to the controllers (such as hand-over, transfer of communication, identification, etc).

In the simulator model, controller actions are described by task. These tasks are basic ATC actions, which are triggered by specific events and have a time value associated with them. This value is the time required in real life for the controller to fulfil the specific action.

The simulator adds the values of the task parameter for a given Test Case and the result value gives an indication of controller workload. Usually, a controller is considered not to be overloaded if this figure does not exceed 70% of the total time of the Test Case.

The precision of workload indication is higher when the ATC modus operandi is better known and formalised, e.g. it could be described by basic task with clearly identified trigger events and well determined time parameters.

Real-Time simulation is used in the later stages of the validation of a proposed design and it may also be used as a way of  demonstrating that both the safety objectives and operational objectives have been met.

Often, the real-time simulation is used as a final check of the design and as the preparatory step for the implementation. This method is used mainly because it provides live feedback from the operational air traffic controller and for its potential high degree of realism.

A Real Time Simulator tries to replicate as accurately as possible the real working environment of involved air traffic controllers.

The main components of a RTS platform are:       

  • simulator engine             
  • active controller positions
  • pseudo pilots and feeder sectors
  • data recording system.

The simulator engine processes the flight plans and the inputs from the pseudo pilots and controllers and provides all positions with replicated data as obtained from operational Radar Data Processing Systems (RDPs) and Flight Data Processing Systems (FDPs).  Use of a research simulator is highly recommended as it allows for the capture of data that a normal ATC simulator does not provide for; however, there a relatively few research simulators in Europe, so pre-planning early in the project is highly recommended.

However, in both real-time and fast-time simulations, aircraft navigation accuracy is shown as being excellent because the tracks are computer generated. To make ATC simulation realistic, particularly those for route spacing, it is necessary to script in navigation errors including shallow and sharp deviations from track. Such errors would need to reflect the current error rate e.g. two errors in ten hours. In addition, if the simulation is looking to assess the use of consistent turn performance, either using RF or FRT, then variation of turn performance should be scripted into the simulation.  This is done to highlight variable turn performance in the current operation so that when RF or FRT are applied in the future environment the controllers will, hopefully, see and recognise the benefit of consistent turn performance.

 

 

Live ATC Trials are probably the least used validation method. Generally, this is because it is perceived as carrying the highest risks despite providing what is probably the highest degree of realism. When used, Live Trials tend to be aimed at assessing a very specific element of an airspace change such as a new SID or STAR or a new Sector design with a very limited traffic sample.

 

 

 

Full flight simulators are renowned for their superior realism and accuracy in reproducing all of the operational characteristics of a specific aircraft type.  Normal and abnormal situations, including all of the ambient conditions encountered in actual flight, can be precisely simulated.  The use of simulators has increased due to advances in technology and the significant cost savings provided by flight simulation training, compared with real flight time. Today’s commercial flight simulators are so sophisticated that pilots proficient on one aircraft type can be completely trained on the simulator for a new type before ever flying the aircraft itself. 

In addition to pilot training, flight simulation has an invaluable role to play in other aeronautical areas, such as research, accident investigation, aircraft design and development, operational analysis, and other activities such as space flight.  Research areas include new concepts, new systems, flying qualities, and human factors.  Most aircraft manufacturers use research simulators as an integral part of aircraft design, development and clearance.  Major aeronautical projects would now be impractical without the extensive use of flight simulation, on both cost and safety grounds.

There are several areas in which the use of a flight simulator, in combination with the other assessment methods, can assist in the successful completion of Terminal Airspace projects.  One example is in the achievement of credibility.  In addition to the well known noise and emission effects on operations on and around runways, environmental issues are now influencing the positioning of routes (and their associated altitude) within the whole of Terminal Airspace at an increasing number of locations due to strong environmental lobby groups.  It is clear that it can be very difficult to convince these groups that their environmental concerns have been addressed fully by the use of mathematical models and/or fast-time simulations – and this is where flight simulators come into their own. 

Using representative aircraft (simulators), the various options for airspace can be extensively flown and data recorded, such as airframe configuration (which affects the noise produced by the aircraft), fuel burn, track miles flown, altitude and so on. Depending on the requirements of a project and the sophistication of the data which is gathered, the results can be fed into analysis software for such parameters as aircraft noise and emissions. 

Apart from intensive, expensive live flight trials, which are normally difficult to integrate with on-going operations, the use of the full flight simulator is the closest to reality.  The credibility factor is further enhanced if operational line pilots are used to fly the flight simulator.  Once the data has been analysed, it can then be presented in the most appropriate way for the target audience.

The increasing importance put on the environmental impact of aviation is a reality. Increasingly, across Europe environmental impact assessments are required when changes are to be made to the ATS routes within a terminal area. The changed placement of any SID STAR/IFP or the introduction of any new procedure is often the biggest single challenge and aircraft noise can be a political issue with local councils.

Noise Modelling use an advanced form of fast-time simulator which is capable of calculating noise contours over a pre-defined area. These ‘noise-modelling’ functionalities are added to typical functionalities (such as a flight trajectory calculation) included in ‘standard’ fast-time simulators.

In order to generate the noise contours for each simulated aircraft in addition to the flight trajectories, the noise modeller determines (according to the aircraft model) the estimated speed and engine power setting/thrust. Based on this data and taking into account the terrain contours and other environmental conditions (time of the day, meteorological condition, etc), the simulator calculates the noise distribution and noise level at predetermined check points.

The accuracy of the results very much depends upon the realism of the aircraft models used by the simulator and on the model used for calculating noise distribution. Aircraft trajectories can be directly derived from recorded Radar data from real-live operations. Even so, modelling individual aircraft is difficult even when using advanced computational technologies.

Movements are allocated to different aircraft ‘types’ and aircraft that are noise ‘significant’ (by virtue of their numbers or noise level) are represented individually by aircraft type. Some ‘types’ are grouped together with those having similar noise characteristics. For each ‘type’, average profiles of height and speed against track distance are calculated from an analysis of radar data. These average profiles are subdivided into appropriate linear segments.

Average ground tracks for each route are calculated based on radar data. Accurate noise exposure estimation requires a realistic simulation of the lateral scatter of flight tracks actually observed in practice. This is done by creating additional tracks which are a number of standard deviations either side of the central average track. The standard deviations and the proportions of traffic allocated to each route are determined by analysis of the radar data.

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