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Identifying Split Failures Due to Over Saturation (Demand> Capacity)

Identifying Split Failures Due to Over Saturation (Demand> Capacity). Ed Smaglik, Darcy Bullock, Jim Sturdevant & Tom Urbanik. Prevailing View. A signal phase does not have periods of over saturation if an agency never sees or hears about problems.

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Identifying Split Failures Due to Over Saturation (Demand> Capacity)

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  1. Identifying Split Failures Due to Over Saturation (Demand> Capacity) Ed Smaglik, Darcy Bullock,Jim Sturdevant & Tom Urbanik

  2. Prevailing View • A signal phase does not have periods of over saturation if an agency never sees or hears about problems. We need tools to tabulate performance metrics related to over saturation 24-7!

  3. Outline • What is saturation? • How do we quantify it? • Yauch v/c ratio • How can we measure it? • Fuhr’s . collect data for better information.. • How should we look at it? • What can we do?

  4. Indianapolis: US 31 & 116th

  5. Saturated or Undersaturated

  6. Split reduction to improve efficiency Under saturated split with slack

  7. Unmet demand at termination Saturated split with no slack

  8. Cycle Based Binning of qg

  9. Need served volume available in real time v/c ratio • Ex.. 30s green on 60s cycle • Sat flow is 1800 vphpl • Observed flow on green/amber is 16 • v/c= 1.06 • … no slack green there • Served vs. Demand Issue

  10. Phase 2, October 18th, 2004

  11. Split Failure? Noblesville site, October 18th, 2004 v/c plots

  12. +5s -5s Split reallocation October 26th October 18th Phase 5 Phase 6

  13. Can we infer Split Failures by estimating served volume to capacity ratios?

  14. Split Failures… counting the dots>1.0

  15. Comments • Before we can manage during over saturation, we need to: • Figure out what we are going to measure • Determine how we can pull some meaningful information out of data • Short term goal: develop tools to enable small, strategic human-in-the-loop to adjustments…without extensive field visits.

  16. Challenges • High Quality Cycle by Cycle Count Data • Detection Technology • Collection on Controller • Quickly extracting meaningful easily understood graphs

  17. Recommended LT Sensor Installation

  18. Questions? Do we mess with PCEs?

  19. Extra

  20. Southbound Count Detectors

  21. Results – Turning Movements

  22. NC1234C EA1234C

  23. Video Detection – Noblesville, IN:Data Collection Cabinet A – Remote Windows Computer for Data Collection B – Video Multi-plexer C – Camera Detector Cards D – Loop Detector Cards E – Patch Panel

  24. Evaluation Location

  25. N

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