Traffic Signal Performance Measures

1. Traffic Signal Performance Measures Presented by Gary Duncan

2. Contributor to this talk • Econolite (ASC 3 Data Logger ) • Gary Duncan • Eric Raamot • Brian Griggs • INDOT (Infrastructure Support and Agency Perspective) • Jim Sturdevant • Jay Wasson • Ryan Gallagher • Indiana LTAP • Neal Carboneau • Jay Grossman (Elkhart County) • Purdue University • Chris Day • Tom Brennan • Ross Haseman • Darcy Bullock

3. Outline Introduction & Collaboration History Need for Performance Measures Seven (7) Draft Performance Measures Detailed discussion of Arterial Coordination Performance Measure Results of a Arterial Case Study Future Efforts by Industry

4. Discussion Points Brief summary of historic intersection performance measurement Overview of the successful Academic/DOT/Industry collaboration used to research enhancements on performance measurement Outline of Product enhancements derived from research

5. Historical Challenges • Typical field data collection has been limited to: • Volume • Occupancy • Average speed • Data averaged over relatively large aggregation periods • Typically 5 - 60 minutes • Controllers have provided some basic MOE logging: • Phase split duration • Reason for termination (Max/Gap/Force Off) • Pedestrian actuation • Transition begin/end • Preemption begin/end

6. 15-minute Average Detector Occupancy

7. High Resolution Data Internal data logger –0.1 second resolution Effective green intervals occur Vehicles move through detection zones

8. High Resolution Data Focus of Today Talk • How can we use high resolution data to • Identify problems in an arterial network • Find ways to improve operations

9. Seven Recommended Performance Measures Culmination of 3 years of collaboration between a INDOT, Purdue University, and NEMA Vendors that participate in the Indiana Market (Econolite is one of them). Extensively validated by Purdue on Econolite ASC 3 controllers deployed along instrumented corridors in Noblesville, Elkhart County, West Lafayette, and Lafayette. Performance measures presented on subsequent slides are drawn from 250,000,000 record database at Purdue that has been archived using Econolite Data Loggers at 15 intersections.

10. FTP Harvesting and SQL Database Ingestion Raw Transport to Purdue Ingest to SQL to Archive INTERNET 8 Remote Indiana ASC/3 Locations Purdue Traffic Lab: Scheduled FTP of High Resolution Traffic Controller Data RAW *.dat Files Downloaded into Temp Folder RAW *.dat Files Processed and ingested into SQL Database Unique Traffic Signal Event Records ingested into SQL 2007 Database *.DAT successfully ingested into SQL are moved from TEMP to ARCHIVE folder

11. Outline Introduction & Collaboration History Need for Performance Measures Seven (7) Draft Performance Measures Detailed discussion of Arterial Coordination Performance Measure Results of a Arterial Case Study Future Efforts by Industry

12. INDOT Signal Network Question INDOT: 2,600 signals in 300 systems Nationwide: 300,000 signals Globally: who knows? Where (and when) are the opportunities to improve signal operations?

13. Outline Introduction & Collaboration History Need for Performance Measures Seven (7) Draft Performance Measures Detailed discussion of Arterial Coordination Performance Measure Results of a Arterial Case Study Future Efforts by Industry

14. Highway Capacity Manual Delay Equation Oversaturation(Split Failures) Quality of Progression(Percent on Green) Capacity Utilization(Volume-to-Capacity Ratio)

15. 1. Cycle Length VCR Scheduling Evaluation

16. 1. Cycle Length (Mismatch) Inconsistent cycle length in system VCR Scheduling Evaluation

17. 2. Equivalent Hourly Flow Rate Are TOD breakpoints in appropriate locations? Are TOD breakpoints in appropriate locations? Are TOD breakpoints in appropriate locations? Are TOD breakpoints in appropriate locations?

18. 3. Green Time Early return Force off min green

19. 4. Volume to Capacity Ratio Many split failures No split failures

20. 5. Split Failures Per Half Hour Many split failures No split failures Number of times that v/c > 1

21. Extensive Detail in subsequent section 6. Purdue Coordination Diagram (PCD)

22. 7. Percentage of Phases with Pedestrians

23. Pedestrian Phasing Concurrent Ped 4/8 Exclusive Ped Phase “9”

24. 0600-2100 Su M Tu W Th F Sa Su M Tu W Th F Sa Missing data 11/13 and 11/14 (days 5/6 in BEFORE)

25. Outline Introduction & Collaboration History Need for Performance Measures Seven (7) Draft Performance Measures Detailed discussion of Arterial Coordination Performance Measure Results of a Arterial Case Study Future Efforts by Industry

26. Evaluating Arterial Progression using PCDs

27. High Resolution Data • How can we use high resolution data to • Identify problems in an arterial network • Find ways to improve operations

28. Purdue Coordination Diagram Construction Loop Detection Time in cycle 120 Cycle boundary Cycle begins Coordination 90 Red Green window 70 Greenphase begins Green phase ends Cycle ends time 50 Green 0 time of day 0 sec 12:00:00 50 sec 90 sec 120 sec 12:02:00 12:00:00 12:01:10 12:02:00 70 sec 12:01:10

29. 30 minute view c384 c388 c389 c390 c391 c392 c393 c394 c395 c396 c397 c383 c385 c386 c387 Clearance red Arrivals in Green Phase 2 Green Primary platoon Phase 1 green Arrivals in Red Phase 2 Red Phase 4 Secondary platoon Phase 3

30. 24-hour view TOD Plan Time Period 1 2 3 4 5 6 7 8 20-pt.moving average b2 a2 a1 b1

31. Relationship between PCD and Flow Profile Fig. 6.9

32. Saturday Performance (June 6, 2009) good 1001 Random arrivals 1002 No platoons bad 1003 good good bad 1004 bad

33. Closer look at three poor arrival patterns NB @ Int. 1002 “Anti-coordination” SB @ Int. 1004 NB @ Int. 1004

34. Modeling Offset Changes Fig. 6.6

35. Example Adjustment NB @ Int. 1002 SB @ Int. 1003 POG = 40.1% POG = 80.2% 5069 arrivals on green(0600-2200) Northbound at 37/Pleasant is bad. The platoon arrives in red. However, any offset adjustments that we make will also impact Southbound progression at 37/Town and Country (intersection to south) by shifting arrivals. We can mitigate any impacts at 32/37 (intersection to north) by adjusting its offset to keep it fixed relative to 37/Pleasant.

36. Add 10 seconds at Int. 1002 +10 s NB @ Int. 1002 SB @ Int. 1003 POG = 55.4% POG = 77.8% 5589 arrivals on green • Green times will occur 10 seconds earlier at 37 & Pleasant • Equivalent to vehicles arriving 10 seconds later • Southbound vehicles will arrive 10 seconds earlier at 37 & Town and Country

37. Add 20 seconds at Int. 1002 +20 s NB @ Int. 1002 SB @ Int. 1003 POG = 67.4% POG = 68.8% 5688 arrivals on green • Green times will occur 20 seconds earlier at 37 & Pleasant • Equivalent to vehicles arriving 20 seconds later • Southbound vehicles will arrive 20 seconds earlier at 37 & Town and Country

38. Add 30 seconds at Int. 1002 +30 s NB @ Int. 1002 SB @ Int. 1003 POG = 73.4% POG = 57.5% 5446 arrivals on green • Green times will occur 30 seconds earlier at 37 & Pleasant • Equivalent to vehicles arriving 30 seconds later • Southbound vehicles will arrive 30 seconds earlier at 37 & Town and Country

39. Offset Optimization

40. Outline Introduction & Collaboration History Need for Performance Measures Seven (7) Draft Performance Measures Detailed discussion of Arterial Coordination Performance Measure Results of a Arterial Case Study Future Efforts by Industry

41. Before good Random OK bad good good bad bad Fig. 6.5

42. Predicted Still OK Random better better good good better better Fig. 6.7

43. ACTUAL OK Random better good good good good good Fig. 6.8

44. Change in Arrivals on Green Table 6.2

45. Before (Sample size=4797)

46. After(Sample size=5401)

47. Cumulative Travel Time –Bluetooth MAC Address Matching ~1.9 min Travel Time Reduction T-value = -5.864P-value > 0.001 Northbound Southbound Independent verification of effectiveness of the operational changes

48. Outline Introduction & Collaboration History Need for Performance Measures Seven (7) Draft Performance Measures Detailed discussion of Arterial Coordination Performance Measure Results of a Arterial Case Study Future Efforts by Industry

49. Future Efforts and Concluding Comments Partnership between Industry, State Agencies, Purdue, and most recently local agencies has resulted in a research result that • Has had measurable impact on arterial operation. • Provided a forum for vetting pictorial performance measures that are understandable by a broad cross section of stake holders • Integrated stake holders in the development process to facilitate rapid deployment by signal vendors • Incorporation of these into specification for a system to be delivered in 2011.