1. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Characterizing the Benefits of Linear Airfield Lighting Elements John D. Bullough RPI Lighting Research Center Troy, NY Nattiel Chambers SRA International, Inc. Linwood, NJ IES Aviation Lighting Committee Fall Technology Meeting Denver, CO · October 18-22, 2015

2. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Outline  Background  Preliminary laboratory and field experiments › Model relating linear element length/spacing to visual acquisition times  Simulator experiment › Comparison with model predictions  Conclusions  Future activities 2 (Gallagher 2005)

3. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Background  Linear/continuous elements for roadway delineation offer benefits to driving safety (Zwahlen and Schnell 1997; Griffith and Brooks 2000; Haas 2004)  Linear airfield lighting elements resulted in increased visual acquisition distances and favorable opinions by pilots (Gallagher 2005; Stauffer and Hyland 2014) 3 (Griffith and Brooks, 2000) (Stauffer and Hyland 2014)

4. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. LRC Experimental Studies  Static images › 2, 8, 32 ft element length › 50, 100, 200 ft spacing 4 › 575 ft viewing distance › Edge lighting (blue)

5. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. LRC Experimental Studies (cont’d.)  In the static image experiments, response times to 2-ft linear elements were strongly correlated to, and not statistically different from, response times to point source taxiway edge lights  For viewing distances of about 575 ft, 2-ft linear elements and point sources provide equivalent visual information 5

6. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. LRC Experimental Studies (cont’d.) 6  Dynamic animations › 2, 8, 32 ft element length › 50, 100, 200 ft spacing › Start 2000 ft away, 50 mph › Centerline lighting (white/green) Correlated (r 2 =0.73) to static image results

7. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. LRC Experimental Studies (cont’d.) 7  Field experiment › 2, 8 ft element length › 25, 100 ft spacing › ~250 ft away › Centerline lighting (green) Correlated (r 2 =0.73) to static image results

8. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Predictive Model: Trading Off Length and Spacing 8 RT (ms) = 286 – 607 log L + 989 log S

9. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. SRA Experimental Study 9  Conducted in FAA’s Airbus A320 cockpit simulator  Clear nighttime conditions simulated

10. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. SRA Experimental Study 10  Goal › Verify accuracy of predictive model under more realistic conditions including: › Taxiing an airplane along an airfield › In the presence of extraneous airfield lights, signs an markings › Include both objective (distance) and subjective (difficulty) outcome measures

11. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Method  Taxiway turnoff intersections having right/left turns and ~90 o /~30 o angles at ORD were selected  Linear centerline lights alternating in green/yellow were located along the intersection  Spacing varied from 50/100/200 ft; length varied from 2/8/32 ft  Conditions were presented in randomized order 11

12. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Procedure  Participants (37 licensed pilots ranging in age from 21-72 years, and with 20/20, 20/25 or 20/30 acuity) taxied between 20-30 knots toward the intersection from at least 2000 ft away  As soon as they could unambiguously identify the side and angle of the intersection, they pressed a button on the side-stick › Distance to the intersection was recorded › At this point they verbally identified the intersection configuration and rated the difficulty in identifying it 12

13. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Example – 2-ft Length 13 2-ft length, 50-ft spacing

14. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Example – 8-ft Length 14 8-ft length, 100-ft spacing

15. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Example – 32-ft Length 15 32-ft length, 200-ft spacing

16. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Another 32-ft Example 16 32-ft length, 50-ft spacing

17. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Overall Results – SRA Experiment 17 Conditions requiring pilots to travel closer to the intersections were rated as more difficult to identify

18. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Effect of Intersection Angle  The 30 o intersections were identified from further away than the 90 o intersections  At 25 knots, the difference corresponds to ~6 seconds of additional time before reaching the intersection 18 Pilots needed to be closer to the 90 o intersection to identify it

19. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Comparisons with LRC Predictive Model 19 RT (ms) = 286 – 607 log L + 989 log S  Response times from the predictive model were positively correlated with the distances pilots traveled in order to identify the intersection configurations

20. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Comparisons with LRC Predictive Model 20 RT (ms) = 286 – 607 log L + 989 log S  Response times from the predictive model were also positively correlated with the ratings of difficulty  Conditions that would require more time to identify were judged as more difficult

21. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Converging Operations 21

22. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Discussion and Conclusions  Linear edge and centerline elements can assist in identifying intersection configurations  The effect is robust and likely related to fundamental visual perception › Static image displays, simple animations, 3D mockups and full cockpit simulators all give consistent results whether edge or centerline › Objective measures like response times and identification distances are very consistent with subjective difficulty measures  It is possible using the predictive model to determine which combinations of length and spacing are equivalent to current practices using point-source lights 22

23. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Ongoing/Future Work  Through FAA’s PEGASAS center, pilots will be evaluating linear lighting configurations under real-world conditions at KOSU, Ohio State University  LRC fabricated a set of LED linear lights that can change in color and length of the luminous element via computer control 23

24. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Ongoing/Future Work (cont’d.)  Pilots will taxi along a runway toward the lights and signal when they can identify the intersection configuration shown  Linear and point-source lights will be used in the field tests 24

25. © 2015 Rensselaer Polytechnic Institute and SRA International, Inc. All rights reserved. Thank You!  Sponsor: Federal Aviation Administration  Don Gallagher (FAA project manager), Robert Booker (FAA), Terence McClain (FAA), Albert Rehman (FAA), Paul Lambert (Rockwell Collins), N. Narendran (LRC), Jean Paul Freyssinier (LRC) 25