http://www.aacn.nche.edu/Publications/issues/Aug02.htm

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an air-to-air system and does not require specialized ground mechanisms to be installedat each airport.

2 Wake Turbulence Aware Altimeter

Given a leading and trailing aircraft, H and T , respectively, our prototype provides newinstrumentation enabling T to proactively avoid the wake turbulence generated by Hin real time. This visual instrumentation of wake turbulence eases demand on air trafficcontrollers while improving safety of aircraft flying within a close spatial and tempo-ral proximity. Data for this system can be acquired through the Automatic DependentSurveillance-Broadcast (ADS-B) protocol [23]; this protocol is widely accepted and ismandated by the FAA to be operational in all general aviation aircraft by 2020, and it isalready widely adopted in Europe.

Our prototype augments an existing altitude strip with additional information aboutthe leading aircraft. Altitude information computed from the leading aircraft, H , isdisplayed as a semi-transparent bar augmenting T ’s existing altitude strip, see Fig.1;as shown, T ’s altitude is currently at 1025ft and the wake turbulence generated byH is currently at 960ft. Thus, T simply needs to hold an altitude above 960ft at itscurrent position to avoid wake turbulence. The graphical representation displays thisdifference of 65ft using the existing altitude strip’s scale/location giving the pilot theability to quickly glance at the altimeter and perceive both values with ease. The pilotof T simply needs to hold the aircraft above the altitude indicated on the wake bar toavoid potential wake turbulence; this holds true for landing, take off, and cruising.

We chose to augment the existing altitude strip to show the leading aircraft’s al-titude information based on input from several pilots from Ohio University’s AvionicsEngineering Center as well as research engineers familiar with rapid prototyping of newcockpit instrumentation. The strip was placed on the right side of the display to mirrorcommon Heads-Up Displays (HUDs), such as those found in Honeywell’s SmartViewflight display [24] and Microsoft Flight Simulator 2011. Strictly speaking, this proto-type does not augment the pilot’s reality via a HUD; instead, the pilot is required toview a display visualizing the augmented reality.

2.1 Implementation via the STEAMiE Visualization Engine

This prototype focuses on the simple case involving only one leading aircraft, H , andone trailing aircraft, T . The more general case involving many aircraft flying indepen-dent courses requires a more sophisticated tracking algorithm and is discussed in section4.

This prototype uses the STEAMiE Visualization Engine [25] to create a syntheticworld which mirrors the real world in real time; this engine has been previously usedto visualize scientific data as well as interactive virtual worlds [26, 27]. In this exper-iment, STEAMiE consumes data from several data sources simultaneously; these in-clude satellite imagery from Microsoft Bing Maps Platform©[28], elevation data fromthe U.S. Geological Survey[29], and real-time flight data from on-board altimeters, on-board GPS receivers, and on-board inertial units. STEAMiE fuses these data into a

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Fig. 1. (Left)Leading aircraft H’s flight path is indicated by the red ribbon; trailing aircraft T ’sflight path is indicated by the blue ribbon. The altitude strip shows the current altitude of T ,and the semi-transparent red bar overlaying the altitude strip shows the altitude of H’s waketurbulence.(Right)Leading aircraft H’s flight path is indicated by the red ribbon; trailing aircraftT ’s flight path is indicated by the blue ribbon. Ohio University’s UNI Airport is visible in thelower right.

Fig. 2. On the right side is leading aircraft H , its red ribbon visualizes its flight path up to thecurrent time. On the left side is trailing aircraft T , its blue ribbon is just out of view in theforefront, but visible in the background as T performed a 180° maneuver.

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Fig. 3. A block diagram showing the inputs and outputs of this prototype. Two STEAMiE in-stances are created; one in the leading and one in the trailing aircraft. The receiving STEAMiEinstance uses information from the transmitting STEAMiE instance in combination with its localinformation to create an augmented virtual world including the enhanced altitude strip.

real-time virtual world accurately portraying the local environment and current flightpath of both aircraft as shown in Figs.1,2; see Fig.3 for a block diagram showing theinputs and outputs. In essence, this virtual world accurately represents reality withinthe time and error bounds of the aforementioned input data sources / devices. Using thedata within this virtual world, an augmented reality including the enhanced altimeteris generated and displayed at 60 frames per second to a monitor mounted in T ’s cock-pit. Furthermore, a colored ribbon of H and T ’s flight paths can be shown within thisworld, see the red and blue ribbons, respectively, as shown in Figs.1,2. The red ribbongenerated by H is the conservative wake turbulence surface. This is the raw data setconsumed by the tracking algorithm described in section 2.2 which populates the wakevalue displayed in the augmented altimeter.

In this prototype, the satellite imagery of the surrounding landscape and elevationdata was displayed to the pilot along with H’s altitude information. In some cases,this may provide unnecessary information to the pilot resulting in visual overload orvisual “noise”; Honeywell’s system, for example, simply shades the terrain removingthe potentially distracting detail of high resolution satellite imagery [24]. In our case,the main focus for this rapid prototype was the wake information and our flight teamwas satisfied using local satellite imagery. Another design decision was to draw verticalplumb lines from the ribbon down to the ground surface; although the wake turbulencemay be avoided by flying far enough below H , it would be impossible for T to maneuverabove H’s wake vortices without changing heading or intersecting the vortices; in the

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case of a final approach, T must approach above H , should T find itself below H ona final, T would be forced to abort the approach, circle around, and attempt final againfrom a higher altitude.

2.2 Tracking Algorithm for Conservative Wake Turbulence Surfaces

This tracking algorithm operates on the position data of H and provides conservativewake turbulence information for the pilot/user. The term conservative in this contextcomes from the wake turbulence model used in this visualization. For this visualization,it is assumed that a wake turbulence is generated at every sampled position of H andremains stationary for a fixed amount of time before dissipating. Except in cases ofsevere updrafts, wake turbulence will only descend; lateral movement is possible, buteven in these cases, reporting the highest nearby point gives a conservative prediction.This is opposed to more high fidelity models, like those explored in [30, 31].

Fig. 4. Two implemented intersection volumes; a semicylinder on the left and a cone on the right(not to scale.)

Nearby can be abstracted to mean “within some intersection volume, within somerecent time interval.” For this prototype, two different intersection volumes have beentested. Visualizations of the two intersection volumes are given in Fig.4.

The first intersection volume tested was a semi-cylinder with its lengthwise axisaligned with the gravity direction of the simulation and centered pointing along theheading vector of T . A radius of one nautical mile was chosen as a safe spatial distancefor wake turbulence avoidance and three minutes was chosen as a safe timeout intervalfor the sampled data points of H .

The semi-cylindrical intersection volume was sufficient in many of the test cases,but one particular case was found where results were too conservative useful. In the casewhere H crosses through the intersection volume twice, flying in opposite directions,but at two different altitudes, the higher altitude will always be taken. This scenariooccurs frequently when one plane is already on their final approach, while the secondplane is flying its base leg (the opposite direction) in preperation of turning onto its

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final approach. Because of lateral movement considerations, this heightened readingis correct under the given constraints, but it was determined that an alternate conicalvolume would be superior in cases involving both planes on their final approach, whichis the situation where this visualization is most valuable.

The conical intersection volume was successful at restricting the search space forwake turbulence in the case outlined above. Because the conical intersection volumeis narrower near T and expands at a distance, it does a better job at predicting likelyturbulence instead of possible turbulence. Because of its shape, the conical intersectionvolume has the same 100% detection rate, on a final approach, as the semi-cylindricalvolume, but produces fewer cautions in situations of possible, but unlikely, wake turbu-lence like the one above.

3 Experimental Results

Fig. 5. Prototype pilot’s cockpit display visualizing the real time virtual world.

The prototype was tested in May 2011 using two aircraft, H and T , based at OhioUniversity’s Snyder Field (UNI). The configurations of H and T are described in sec-tions 2 and 2.1 are summarized in Fig.3. The flight configuration involved H approach-ing the runway from 10NM while T circled at a distance of 5−7NM from the runway.When H approached the ~7NM mark, T performed a standard “base leg” maneuver toposition itself about 1NM behind H matching H’s flight direction. At the point whereT ’s semicircle-based inclusion region began intersecting with H’s conservative waketurbulence surface, T ’s wake strip began displaying the corresponding altitude of H’swake vortices; see Fig.1 and Sec.2.2. The cockpit mounted display shown in Fig.5 isthe prototype’s output and pilot’s input.

The specific altimeters used gave a 10ft resolution at 1Hz, H’s GPS update fre-quency was 1Hz, and H’s 329Mhz/1200 baud transmitter sent the pseudo ADS-Bmessage to T at 5Hz; this higher transmit frequency implied that only 1 out of 5 relatedtransmits needed to be received properly by T to update at the maximum frequency of

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Fig. 6. Screen shots showing T converge on the runway while visualizing H’s conservative waketurbulence surface and corresponding wake strip on the altimeter.

H’s altimeter and GPS. This was useful when the system was operating at the maxi-mum tested range of about ~13NM ; the system did not ever lose communication forany extended period of time.

T ’s GPS was integrated with a 100Hz inertial unit and used a Kalman filter to in-terpolate its GPS position at 100Hz; therefore, T moved with a smooth position andorientation, including smooth updates to the pitch ladder as shown in Fig.6. The ac-tual virtual world was displayed at 60Hz to the pilot; as a result, the display shownin Figs.5 and 6 was virtually indistinguishable from commercial flight simulation soft-ware, with the exception that this represented the current state of the real world. For abrief YouTube video of the actual test flight and one of the synthetic world output, see[32, 33], respectively.

4 Conclusion and Future Work

Our flight tested prototype successfully provided the pilot with a real-time instrumentto more precisely avoid wake turbulence from a leading aircraft; as was the originalintent of this research. The necessary data for this prototype is available via the FAAmandated ADS-B protocol and therefore requires no new communications equipmentto be installed[23]. Ohio University’s Avionics Engineering Center’s acting Chief PilotJamie Edwards, described his experience with the prototype, “The displayed wake stripinformation gives a pilot actual guidance to stay above the flight path of the aircraftahead of him. It can give the pilot of the light aircraft in this situation a peace-of-mindnever known before.” He further described the prototype’s usage during flight, “Thered wake strip concept is intuitive to fly. It overlays the altitude strip and gave me adirect indication as to my vertical position relative to the aircraft in front of me whenhe was at my same distance from the airport. It easily allowed me to set a descent ratethat kept the red wake strip below my current altitude and effectively clear of his waketurbulence.”

Future work will focus on extending the tracking algorithm to multiple aircraft andclearly conveying this information to the pilot in an intuitive manner without causing

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“information overload.” Furthermore, we would like to enhance the synthetic world toquickly give the pilot wake turbulence information for all local air traffic which willdecrease necessary aircraft spacing, increase airport capacity, minimize airport con-gestion, and relieve wake turbulence related air traffic control responsibilities whileimproving overall safety.

Finally, we intend to incorporate more advanced wake turbulence models, such asthose found in [30, 31], and compare trade offs between the additional aircraft densityallowed by these models and safety.

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