Arterial Corridor Active Management Measures for Winter Operation and System Analysis

1. Arterial Corridor Active Management Measures for Winter Operation and System Analysis April 7th, 2010 Hilton Garden Indianapolis, IN

2. Seven RecommendedPerformance Measures

3. 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?

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

5. 1. Cycle Length VCR Scheduling Evaluation

6. 1. Cycle Length Inconsistent cycle length in system VCR Scheduling Evaluation

7. 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?

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

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

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

11. 6. Purdue Coordination Diagram (PCD)

12. 7. Percentage of Phases with Pedestrians

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

14. 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)

15. Offset Optimization using PCDs

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

17. Poor offsets or random arrivals? 100% Pretty bad Percent on Green Pretty good Why? 0% Saturday cycle-by-cycle percent on green,NB @ 32/37 (2009 ITE dinner presentation)

18. Why poor progression? space Cycle Length Green Band 1. Random arrivals – no upstream coordination – no platoons time

19. Why poor progression? space Cycle Length Green Band P = 38% P = 75% 2. Poor offset (Adjusted) time

20. 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

21. 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

22. 24-hour view TOD Plan Time Period 1 2 3 4 5 6 7 8 20-pt.moving average b2 a2 a1 b1

23. Relationship between PCD and Flow Profile Fig. 6.9

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

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

26. Modeling Offset Changes Fig. 6.6

27. 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.

28. 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

29. 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

30. 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

31. Offset Optimization

32. Offset Optimization O1001 O1002 O1003 O1004 Cn = 1144 = 168 Million Combinations • “Hierarchical Heuristic Search” • Reduce the complexity by reducing the resolution of the search • Consider only offset adjustments of {-40, -20, 0, +20, +40, +60} • Once optimal point is found from that set, “fine-tune” by considering small adjustments to the offsets • Objective: Maximize Number Arriving on Green (Ng) • Will discuss in detail later • This procedure not scalable

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

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

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

36. Change in Arrivals on Green Table 6.2

37. Before (Sample size=4797)

38. After(Sample size=5401)

39. 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

40. Offset Optimization Methodologies Revisited concepts to developLink Pivoting algorithm • TRANSYT (1960s-present): “Hill-climbing” algorithm • Adjusts offsets in iterative process until no further improvement is obtained • Sensitive to initial settings • Combination Method (1960s-1970s) • Reduces network by making series/parallel “combinations” • SIGOP (1960s-1980s): Monte Carlo simulation • Select offsets at random and refine to develop a set of solutions • Select best solution for implementation • Synchro (1990s-present) • Coordinatability factor • Quasi-exhaustive search

41. Link Pivoting Concept +20 s Delay-offset relationship at Int. 1003 after upstream adjustment +20 s Delay-offset relationship at Int. 1003

42. Link Pivoting Algorithm 1001 1002 1003 1004 • Step 0 • Existing system state

43. Link Pivoting Algorithm 1001 1002 Number on Green -39 1003 Offset Adjustment @ 1001 1004 • Step 1 • Set O1005 • Impacts highlighted link

44. Link Pivoting Algorithm 1001 1002 Let’s look at this step in more detail Number on Green 1003 Offset Adjustment @ 1002 1004 • Step 2 • Set O1004 • Impacts highlighted link

45. Link Pivoting Algorithm 1001 1002 Number on Green –40 1003 Offset Adjustment @ 1002 1004 • Step 2 Trial Value • Set O1004 • Impacts highlighted link

46. Link Pivoting Algorithm 1001 1002 Number on Green –20 1003 Offset Adjustment @ 1002 1004 • Step 2 Trial Value • Set O1004 • Impacts highlighted link

47. Link Pivoting Algorithm 1001 1002 Number on Green +0 1003 Offset Adjustment @ 1002 1004 • Step 2 Trial Value • Set O1004 • Impacts highlighted link

48. Link Pivoting Algorithm 1001 1002 Number on Green +20 1003 Offset Adjustment @ 1002 1004 • Step 2 Trial Value • Set O1004 • Impacts highlighted link

49. Link Pivoting Algorithm 1001 1002 Number on Green +40 1003 Offset Adjustment @ 1002 1004 • Step 2 Trial Value • Set O1004 • Impacts highlighted link

50. Link Pivoting Algorithm 1001 1002 Number on Green -7 1003 Offset Adjustment @ 1002 1004 • Step 2 • Set O1004 • Impacts highlighted link