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NDOR Research Conference: Dr. Rilett

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Nebraska Department of Roads Conference 2012
Presented by Dr. Larry Rilett

Published in: Automotive, Technology, Education
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NDOR Research Conference: Dr. Rilett

  1. 1. Evaluation of NDOR’s Active Advance Warning System Laurence R. Rilett Ph.D., P.E. University of Nebraska-Lincoln
  2. 2. Presentation Outline• Background• Analyses – Safety – Operation – Simulation – Sensitivity• Conclusions• Recommendations
  3. 3. Background• Dilemma Zone – At the legal speed limit, the driver can neither clear the intersection before the end of the intergreen period nor stop without entering the intersection.
  4. 4. Background• Dilemma Zone: NDOR 2002 Report – “Length of roadway in advance of the intersection wherein drivers may be indecisive or respond differently to the onset of the yellow indication.” – Also known as “option zone” or “zone of indecision”
  5. 5. Background• If an intersection is designed correctly (e.g. NDOR) a dilemma zone will not exist – Assuming deterministic system• Vehicles same characteristics (accelerate, decelerate, weather, etc.) – Trucks/braking• Drivers make the correct decisions – Stop, proceed• Assuming: legal maneuvers (not running red light)
  6. 6. Potential Problems• A major safety concern at high speed signalized intersections
  7. 7. Common Treatments• Advance Warning (AW) Flashers – Flashing signal heads and warning signs • Activated at predetermined time before end of green• “Mixed” results regarding effectiveness
  8. 8. Common Treatments• Advance Detection (AD) – Series of detectors in advance of intersection • Extend green on detection – Effective in reducing crashes and conflicts – Increases likelihood of extending green to maximum (max-out) • Dilemma zone protection is lost
  9. 9. NDOR’s Actuated AdvanceWarning (AAW) System• Combines advance detection and advance warning – Single detector – Shorter maximum allowable headway – Lower frequency of max-out
  10. 10. Issues• Results positive but mostly anecdotal• Guidelines for installation – When do they need to be removed (if ever)?• Motivation for study
  11. 11. Part 1Crash Data Analyses
  12. 12. Safety Effectiveness• Test Sites – 26 treated intersections – 29 reference intersections • “Similar” characteristics as treated intersections • Provided by NDOR – 13 year of crash counts and AADT • 1996-2008
  13. 13. Treated Intersections: Table2.2 Simple example ignores regression to mean, changes in AADT… Need to compare to untreated intersections…
  14. 14. Safety Effectiveness• Method – Full Bayes – Accounts for uncertainty in data – Generates a distribution of likely expected number of crashes – Combines this distribution with site-specific crash data to obtain expected crash frequency – Approach is complex but requires less data
  15. 15. Safety Effectiveness• Crash Reduction Rate
  16. 16. Safety Effectiveness• Model
  17. 17. Safety Effectiveness Results
  18. 18. Safety Effectiveness Results
  19. 19. Safety Effectiveness Results
  20. 20. Safety Effectiveness Results
  21. 21. Safety Effectiveness Results
  22. 22. Safety Effectiveness Results
  23. 23. Safety Effectiveness Results
  24. 24. Safety Effectiveness Results
  25. 25. Part 2Operational Analyses
  26. 26. Operational Analyses• Main Characteristics – Approach speeds – Acceleration/deceleration characteristics • Following onset of yellow • During lead flash – Frequency of max-outs – Rate of dilemma zone “entrapment” – Waiting time on conflicting phases
  27. 27. Study Site: Lincoln• Highway 77 and Saltillo Road
  28. 28. Study Site: Omaha• Highway 370 and N 132nd Street
  29. 29. Operational Analyses• Data
  30. 30. Operational Analyses• Max-out probabilities
  31. 31. Operational Analyses• Waiting time on minor road
  32. 32. Operational Analyses• Waiting time on minor road
  33. 33. Lincoln (Figure 3.13)• Acceleration/deceleration- lead flash
  34. 34. Omaha• Acceleration/deceleration- lead flash
  35. 35. Operational Analyses• (Average) speed profile- lead flash
  36. 36. Operational Analyses• Acceleration/deceleration- yellow
  37. 37. Operational Analyses• Acceleration/deceleration- yellow
  38. 38. Operational Analyses• (Average) speed profile- yellow
  39. 39. Operational Analyses• Vehicles in dilemma zone- yellow
  40. 40. Part 3Microsimulation Analyses
  41. 41. Microsimulation Model• VISSIM – Inputs: geometry, traffic counts, timing, speeds, etc.• Calibration – Adjust model parameters such that field data “matches” simulated data – Measures of performance • Average waiting time • Speed profile
  42. 42. Microsimulation Model• GA Calibration Procedure
  43. 43. Microsimulation Model• Calibration Results
  44. 44. Microsimulation Model• Measures of performance – Average waiting time
  45. 45. Microsimulation Model• Measures of performance – Speed profile
  46. 46. Sensitivity Analysis• Experimental Design
  47. 47. Sensitivity Analysis• Simulation runs – 480 total factor combinations – 1-hour simulation run for each – 10 replications each• Output – Waiting times – Number of conflicts
  48. 48. Sensitivity Analysis• Effect of turn percentage – On average waiting times
  49. 49. Conclusions• Safety effects – Greater than 90% probability that installation of system is beneficial• Operational effects – Lower than expected number of vehicles in dilemma zone – Low max-out probabilities – System seems to work well
  50. 50. Conclusions• Simulation model – Developed framework for modeling system – Successfully applied to two sites• Sensitivity analysis – Site specific – Can be used to perform sensitivity analyses
  51. 51. Recommendations• System worth considering at other high-speed signalized intersections – From a safety perspective• Guidelines regarding installation – McCoy and Pesti (2002)• Guidelines regarding removal – Simulation study • Max out, delay, etc.
  52. 52. CREDITSDr. Laurence Rilett, Ph.D., P.E. University of Nebraska-LincolnSlide design © 2009, Mid-America Transportation Center. All rights reserved.

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