Improving Aviation Safety with Information Visualization: Airflow Hazard Display for Pilots Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006

Improving Aviation Safety with Information Visualization:

Airflow Hazard Display for Pilots

Cecilia R. AragonIEOR 170

UC Berkeley

Spring 2006

Spring 2006 IEOR 170 2

Acknowledgments

• This work was funded by the NASA Ames Full-

Time Graduate Study Program (Ph.D. in

Computer Science at UC Berkeley)

• Thanks to my advisor at UC Berkeley, Professor

Marti Hearst, and Navy flight test engineer

Kurtis Long

• Thanks to Advanced Rotorcraft Technology, Inc.

for the use of their high-fidelity flight simulator


Talk Outline

• Introduction

• Related Work

• Preliminary Usability Study

• Flight Simulation Usability Study

• Conclusions and Further Work


Introduction


Motivation

• Invisible airflow hazards cause aircraft accidents – Wind shear– Microbursts– Vortices (turbulence)– Downdrafts– Hot exhaust plumes

• Crash of Delta Flight 191 at DFW 1985 (microburst)• NTSB database 1989-99

– 21,380 aircraft accidents– 2,098 turbulence/wind related




The Problem

• Invisible airflow hazards cause aircraft accidents– Air is invisible, so pilots can’t see hazards– If air flows past obstacles, flow will become more

turbulent

• Helicopters are especially vulnerable– Rotorcraft aerodynamics– Must operate in confined spaces– Operationally stressful conditions (EMS, military

operations, shipboard operations)


A Possible Solution

• If pilots could see hazards, could take appropriate action• New lidar technology suggests a solution

– Lidar (light detection and ranging) is essentially laser radar. A laser transmits light which is scattered by aerosols or air molecules and then collected by a sensor. Doppler lidar can detect the position and velocity of air particles.

• My research focuses on the human interface -- how to visualize the sensor data for pilots -- too much information could overload pilot during critical moments


Research Approach

• User-centered (iterative) design process• Simulated interface for head-up display (HUD)

based on lidar sensors that scan area ahead of helicopter and acquire airflow velocity data

• Focused on helicopter-shipboard landings• Importance of realism:

– Used actual flight test data from shipboard testing, high-fidelity helicopter simulator, experienced military and civilian helicopter pilots


Rationale for using Shipboard Landings

• Why focus on helicopter shipboard landings?– Problem is real: dangerous environment, want to improve

safety

– Ship superstructures always produce airwake

• Large quantities of flight test data due to

demanding environment


Related Work


Related Work

• Flow visualization• Aviation displays• Navy “Dynamic Interface” flight tests


Flow visualization

• Detailed flow visualizations designed for scientists or engineers to analyze at length

• Much work has been done in this area [Laramee et al 04]– Streamlines, contour lines (instantaneous flow) [Buning 89], [Strid et

al 89], [Helman, Hesselink 91]– Spot noise [van Wijk 93], line integral convolution [Cabral, Leedom

93], flow volumes [Max, Becker, Crawfis 93], streaklines, timelines [Lane 96], moving textures [Max, Becker 95] (unsteady flow)

– Automated detection of swirling flow [Haimes, Kenwright 95]– Terrain and turbulence visualization [LeClerc et al 02]

• But usually no user tests [Laidlaw et al 01], andnot real-time


Aviation displays

• Synthetic and enhanced vision and augmented-reality displays [Hughes et al 02], [Parrish 03], [Spitzer et al 01], [Kramer 99], [Wickens 97]

• Weather visualization, microburst detection [NASA AWIN, TPAWS], [Latorella 01], [Spirkovska 00], turbulence detection/prediction [Britt et al 02], [Kaplan 02]

• Wake vortex visualization [Holforty 03]


Navy Ship-Rotorcraft Compatibility Flight Testing (“Dynamic Interface”)

• Very hazardous environment [Wilkinson et al 98]• Significant amounts of flight testing [Williams et

al 99]• Recognized need for pilot testing• Goal: improve safety


Current state of the art

• Ship/helicopter flight tests, wind tunnel tests, CFD

• Develop operational envelopes– Limit allowable landing

conditions significantly– Envelopes are conservative

for safety reasons

• Pilots use intuition, but accidents still occur


Preliminary Usability Study


Preliminary usability study: goals

• Assess efficacy of presenting airflow data in flight

• Obtain expert feedback on presentation of sample hazard indicators to refine design choices


Usability study: low-fidelity prototype

• Rhino3D (3D CAD modeling program)– Easy access to ship models, ease of rapid prototyping– Chosen over 2D paper prototype, MS Flight

Simulator, WildTangent, VRML-based tools, Java and Flash

• Series of animations simulating helicopter’s final approach to landing

• Different types of hazard indicators• Get pilot feedback and suggestions (interactive

prototyping)


Low-fi usability study screen shots


Low-fi usability study screen shots


Low-fi usability study participants

• Navy helicopter test pilot, 2000 hours of flight time, 17 years experience

• Navy helicopter flight test engineer, 2000+ hours of simulator time, 100 hours of flight time, 17 years experience

• Civilian helicopter flight instructor, 1740 hours of flight time, 3 years experience


Low-fi usability study results

• All participants said they would use system• Feedback on hazard indicators:

– Color: all preferred red/yellow only

– Transparency: should be visible enough to get attention, but must be able to see visual cues behind it

– Depth cueing: all preferred shadows below object, #1 said shadows alone sufficient. #2 wanted connecting line. No one wanted tick marks or numeric info.

– Texture: #1, #2 didn’t want. #3 suggested striping

– Shape: Rectilinear and cloud shapes favored. Keep it simple! Watch for conflicting HUD symbology.


Low-fi usability study results (cont’d)

• Motion is distracting!1: absolutely no motion

2: didn’t like motion

3: slow rotation on surface of cloud OK, nothing fast


Low-fi usability study conclusions

• They want it!• Keep it simple

– Color: red & yellow only (red = danger, yellow = caution)– Less complex shapes preferred

• Use accepted symbology/metaphors– Watch for conflicting HUD symbology

• Decision support system, not scientific visualization system– Show effects rather than causes– Don’t want distraction during high-workload task– Preference for static rather than dynamic indicators

Flight Simulation Usability Study


Flight Simulation Usability Study

• Implement visual hazard display system in simulator based on results from low-fidelity prototype

• Advanced Rotorcraft Technology, Inc. in Mountain View, CA, USA– High-fidelity helicopter flight simulator– Accurate aerodynamic models

• Use existing ship and helicopter models, flight test data

• Simulated hazardous conditions, create scenarios, validated by Navy pilots and flight engineers


Flight Simulation Usability Study: Participants

• 16 helicopter pilots– from all 5 branches of the military (Army, Navy, Air Force,

Coast Guard, Marines)

– civilian test pilots (NASA)

– wide range of experience• 200 to 7,300 helicopter flight hours (median 2,250 hours)

• 2 to 46 years of experience (median 13 years)

• age 25 to 65 (median age 36)

• No previous experience with airflow hazard visualization


Simulation Experiment Design• 4 x 4 x 2 within-subjects design (each pilot flew

the same approaches)• 4 shipboard approach

scenarios

• 4 landing difficulty levels (US Navy Pilot Rating Scale - PRS 1-4)

• Each scenario was flown at all difficulty levels both with and without hazard indicators

• Orders of flight were varied to control for learning effects


Airflow Hazard Indicators in Simulator


Simulation Experiment Design

Red/NoneTest benefit of hazard indicator combined with pilot SOP

Controllability in question; safe landings not probable

LD 4

Yellow/NoneTest benefit of hazard indicator

Maximum pilot effort required; repeated safe landings may not be possible

LD 3

Yellow/NoneTest negative effects of hazard indicator

Moderate pilot effort required; most pilots able to land safely

LD 2

NoneControlNo problems; minimal pilot effort required

LD 1

Hazard indicator

PurposeDescriptionLanding difficulty



Dependent Variables

• Objective data: sampled at 10 Hz from simulator– aircraft velocity and position in x, y, z– lateral and longitudinal cyclic position and velocity– collective and pedal positions and velocities– landing gear forces and velocities– (A “crash” was defined as an impact with the ship

deck with a vertical velocity of more than 12 fps)

• Subjective data: 21-probe Likert-scale questionnaire administered to pilots after flight


Hypotheses1. Crash rate will be reduced by the presence of

hazard indicator (LD 3).

2. Crashes will be eliminated by red hazard indicator if a standard operating procedure (SOP) is given to the pilots (LD 4).

3. Hazard indicator will not cause distraction or degradation in performance in situations where adequate performance is expected without indicator (LD 2).

4. Pilots will say they would use airflow hazard visualization system


Hypothesis 1 confirmed

• Presence of the hazard indicator reduces the frequency of crashes during simulated shipboard helicopter landings (t-test for paired samples, t=2.39, df=63, p=0.00985). 19% --> 6.3%

Landing Difficulty 3:Crash Rate vs. Presence of Hazard

Indicator

0.00

0.05

0.10

0.15

0.20

0.25

Absent Present

Hazard Indicator

Cra

sh

Ra

te


Hypothesis 2 confirmed

• Presence of the red hazard indicator combined with appropriate instructions to the pilot prevents crashes (t=4.39, df=63, p < 0.000022). 23%-->0%

Landing Difficulty 4:Crash Rate vs. Presence of Hazard Indicator

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

Absent Present

Hazard Indicator

Cra

sh

Ra

te


Hypothesis 3

• No negative effect of hazard indicator. 8%-->8%

Landing Difficulty 2:Crash Rate vs. Presence of Hazard Indicator

0.00

0.02

0.04

0.06

0.08

0.10

0.12

Absent Present

Hazard Indicator

Cra

sh R

ate


Hypothesis 3 (cont’d)

• Pilots believe hazard indicators were not distracting (Probe 6 results).

6. The airflow hazard visualization distracted me from the task of flying the aircraft.

0

2

4

6

8

10

12

StronglyDisagree

Disagree Neither AgreeNor Disagree

Agree StronglyAgree

Pilot response

6% Agree, 94% DisagreeMedian 2, Std Dev 0.7

Nu

mb

er

of

resp

on

ses


Hypothesis 4 confirmed• Pilots would use the system (Probe 21 results).

21. I would use this display system if it were available on my aircraft.

0

1

2

3

4

5

6

7

8

9

StronglyDisagree


Agree StronglyAgree

Pilot response

81% Agree, 13% DisagreeMedian 4.5, Std Dev 1.0

Nu

mb

er

of

resp

on

ses


Pilot workload:Power spectrum analysis of control inputs


Go-Arounds (Aborted Landings)

• Does the presence of the hazard indicator increase the go-around rate?

• No significant differences found.

LandingDifficulty

HazardIndicator

Go-Arounds

TotalApproaches

Go-AroundRate

StandardError

LD 1 No 3 64 0.0469 0.0266

No 17 64 0.266 0.0556LD 2

Yellow 12 64 0.188 0.0492

No 22 64 0.344 0.0598LD 3

Yellow 23 64 0.359 0.0605


Analysis by Pilot Experience Level

• Does pilot experience level have any effect on the benefits produced by the hazard indicators?

• To find out, divide pilots into three groups:

Pilot ExperienceLevel

Helicopter FlightHours

Number of Pilots inGroup

Less experienced 200 – 850 5

Moderatelyexperienced

1500 – 3200 7

Highly experienced 4000 - 7300 4


Analysis by Pilot Experience Level (cont’d)• Same general trends -- but small sample size• No significant difference between the groups

0

0.05

0.1

0.15

0.2

0.25

Crash Rate

Low Mod Hi

Pilot Experience Level

Crash Rate vs. Experience Level

LD 2/No

LD 2/Haz

LD 3/No

LD 3/Haz

LD 4/No

LD 4/Haz


Analysis of Subjective Data• 94% found hazard indicators helpful

18. The presence of the hazard indicators gave me more confidence as to the state of the winds and

airwake on deck.

0123456789

StronglyDisagree


Agree Strongly Agree

Pilot response


Nu

mb

er

of

res

po

ns

es


Analysis of Subjective Data (cont’d)

• Is motion (animation) helpful or distracting?14. It would be distracting if the hazard indicator

showed airflow motion.

0

1

2

3

4

5

6

7

8

9

StronglyDisagree


Agree Strongly Agree

Pilot response


Nu

mb

er o

f re

spo

nse

s


Conclusions and Further Work


Conclusions

• Flight-deck visualization of airflow hazards yields

a significant improvement in pilot ability to land

safely under turbulent conditions in simulator

• Type of visualization to improve operational

safety much simpler than that required for

analysis

• Success of user-centered design

procedure


Further Work

• Additional data analysis

• Further studies

• Steps toward system deployment

• Extensions to other areas


Additional data analysis

• Power spectrum analysis of control input

data

• Flight path deviations and landing

dispersion

• Quantitative measures of landing quality


Further studies

• Quantitatively compare hazard indicators with other types– light/buzzer in cockpit– animated indicator– numeric information such as airflow velocity

• Adaptive displays– more detailed at beginning of approach, simpler at

end– how adapt to pilot state? physiological sensors vs.

pilot-selectable modes


Steps toward system deployment

• Collaboration with lidar developers,

integration with real-time data

• Integration with synthetic vision displays

• Augmented reality image registration


Extensions to other areas

• Other aviation domains– aerial firefighting– search and rescue– offshore oil platforms– unmanned aerial vehicles (UAVs)– fixed-wing operations

• Space exploration• Emergency response• Automobiles or other motor vehicles


Extra Slides


Crash Statistics for All Landing Difficulties

LandingDifficulty

HazardIndicator

CrashesTotal

ApproachesCrashRate

StandardError

LD 1 No 6 64 0.0938 0.0367

No 5 64 0.0781 0.0338LD 2

Yellow 5 64 0.0781 0.0338

No 12 64 0.188 0.0492LD 3

Yellow 4 64 0.0625 0.0305

No 15 64 0.234 0.0534LD 4

Red 0 64 0 0


Control group (LD 1)

• No significant difference between crash rate at LD 1 (control) and LD 2 with hazard indicator and LD 3 with hazard indicator. 9% - 8% - 6%

Comparison of Crash Rates at Landing Difficulty 1 with Rates at LD 2 and 3 with Hazard Indicator Present

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

LD 1/No Haz Indicator LD 2/Haz Indicator Present LD 3/Haz Indicator Present

Landing Difficulty (LD) and Presence/Absence of Indicator

Cra

sh

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Learning Effects?

• First half: 25 crashes/224; second half: 22/224.• Not a significant difference --> no apparent bias.

Number of crashes as a function of approach order

0

1

2

3

4

5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

Approach - order flown

Nu

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ou

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Airflow Hazard Indicator (Aft Scenario)


Airflow Hazard Indicator (Bow Scenario)


Pilot EmployerHelicopter

HoursAge

Years ofExperience

Number ofShipboardLandings

1 Coast Guard 800 30 3 40

2 Coast Guard 1500 28 5.5 60

3 Coast Guard 770 26 2.5 200



6 Coast Guard 5600 43 22 1000

7 NASA 3100 59 46 100

8Air Force/Air

National Guard3000 37 18 18

9Air Force/Air


10 NASA 2500 65 35 302

11 Army, civilian 4300 56 34 6

12Air Force/Air


13 Army, NASA 7300 51 29 150

14 Air Force, NASA 4000 60 36 0

15 Navy, Marines 3200 41 18 1500

16 Marines 850 33 8 600

Pilot Demographics















Low-fi usability study: methodology

• 1 ½-hour interview in front of projection screen, videotaped

• Two experimenters, one operates computer, one asks questions

• Display series of hazard indicators in Rhino3D • Variables:

– Shape– Color– Transparency– Texture– Depth cueing– Motion

• Ask specific and open-ended questions throughout the interview


“The Holy Grail” – Quote from Pilot #1

• “The holy grail…”– increase safety and– increase operational capability

• Usually you either have:– increased safety but have operational

restrictions…or– greater operational capability but have risks

associated with employing that additional capability...

• “In this case you actually have a concept that could potentially give you both.”

Documents

Improving Aviation Safety with Information Visualization: Airflow Hazard Display for Pilots Cecilia R. Aragon IEOR 170 UC Berkeley Spring 2006