1. 1 Arterial Performance Measurement Mathew Berkow, Michael Wolfe, Christopher Monsere and Robert L. Bertini Intelligent Transportation Systems Laboratory Maseeh College of Engineering and Computer Science Portland State University Arterial Performance Measurement Using Transit AVL and Signal System Data

2. 2 Arterial Performance Measurement Introduction  Develop an automated way to report speeds, travel times and performance measures using:  Existing ITS signal infrastructure  Automatic Vehicle Locator (AVL) data  Expand PORTAL to include arterial data  Develop an automated way to report speeds, travel times and performance measures using:  Existing ITS signal infrastructure  Automatic Vehicle Locator (AVL) data  Expand PORTAL to include arterial data

3. 3 Arterial Performance Measurement PORTAL -- Regions ADUS

4. 4 Arterial Performance Measurement What’s in the PORTAL Database? Loop Detector Data 20 s count, lane occupancy, speed from 500 detectors (1.2 mi spacing) Incident Data 140,000 since 1999 Weather Data Every day since 2004 VMS Data 19 VMS since 1999 Days Since July 2004 About 300 GB 4.2 Million Detector Intervals Bus Data 1 year stop level data 140,000,000 rows 001703 WIM Data 22 stations since 2005 30,026,606 trucks Crash Data All state-reported crashes since 1999 - ~580,000

5. 5 Arterial Performance Measurement What’s Behind the Scenes? Database Server PostgreSQL Relational Database Management System (RDBMS) Storage 2 Terabyte Redundant Array of Independent Disks (RAID) Web Interface

6. 6 Arterial Performance Measurement Selected Arterial Performance Measures

7. 7 Arterial Performance Measurement Inspiration – Signal System Data Only

8. 8 Arterial Performance Measurement Inspiration – Bus AVL System Data Only I-5 I-205 US 26 SR 217 Powell Blvd.

9. 9 Arterial Performance Measurement Powell Blvd. Corridor Study

10. Study Corridor  Four-lane arterial  3 Miles  East-West  50,000 ADT

11. TriMet’s Bus Dispatch System (BDS) On- Board Computer Radio Doors Lift APC (Automatic Passenger Counter) Overhead Signs Odometer Signal Priority Emitters Memory Card Radio System Garage PC’s Radio Antenna GPS Antenna Navstar GPS Satellites Control Head

12. BDS Data  Route Number  Vehicle Number  Service Date  Actual Leave Time  Scheduled Stop Time  Actual Arrive Time  Operator ID  Direction  Trip Number  Bus Stop Location  Dwell Time  Door Opened  Lift Usage  Ons & Offs (APCs)  Passenger Load  Maximum Speed on Previous Link  Distance  Longitude  Latitude

13. Probe Vehicle Location Over Time

14. 39TH DIVISION 26TH 33RD 1ST 21ST FRANCIS 11TH LINCOLN HARRISON 20TH MILWAUKIE 14TH 13TH 3-D Speed Contour Time Distance

15. 3-D Speed Contour

16. Conceptual Bus  Hypothetical Bus – run without stops or passenger activities (no dwell)  Pseudo Bus – travel at maximum achieved speed record within link  Modified Pseudo Bus – travel at maximum achieved speed with additional time spent at stops

17. 0 0.5 1 1.5 2 2.5 3 7:07:00 AM7:12:00 AM7:17:00 AM Time Distance (miles) Bus Hypothetical Bus Pseudo Bus Modified Pseudo Bus Ross Island Bridge Thurs. Nov. 1, 2001 BUSHypo Pseudo Modified Stop circle

18. 0 0.5 1 1.5 2 2.5 3 1:04:00 PM1:09:00 PM1:14:00 PM Time Distance (miles) Ross Island Bridge Test Vehicle Bus Hypothetical Bus Pseudo Bus Modified Pseudo Bus Bus Hypo Pseud o Modified Pseudo Vehicle

19. Test Vehicles vs. Buses

20. Test Vehicle vs. Pseudo

21. Ross Island Bridge Four-lane traffic (2 lane on both side) No shoulders Approaches are bottleneck No interruptions No bus stops

22. Test Vehicle vs. Pseudo

23. 23 Arterial Performance Measurement This Project: Combine Signal and Bus AVL

24. 24 Arterial Performance Measurement This Project: Combine Signal and Bus AVL

25. 25 Arterial Performance Measurement Past and Ongoing Efforts  Using stop bar detectors to generate an arterial performance map  Hallenbeck, Ishimaru, Davis, Kang  Liang  Performance based on summation of delay components  Liu, Ma  Skabardonis, Geroliminis  Intersection/Signal Performance  Sharma, Bullock, Bonneson  Smaglik, Bullock, Sharma

26. 26 Arterial Performance Measurement DD Signal System Data: Portland’s Detection Infrastructure Data Aggregation  Count Station 5 min  Other Detector 15 min  7 Day Sample

27. 27 Arterial Performance Measurement Case Study: Barbur Blvd. Speed Map Sheridan Hooker Hamilton 3rd Terwilliger Bertha 19th I-5 Off-ramp 30th Park & Ride N

28. 28 Arterial Performance Measurement Will It Work? To The Video….

29. 29 Arterial Performance Measurement Detectors at Barbur and Bertha

30. 30 Arterial Performance Measurement Density vs. Occupancy   Density = number of vehicles per distance   Occupancy = percent of time with a vehicle on the sensor   Density = Occupancy X 1/(vehicle length + sensor length) Density = 2 vehicles / 45 feet =.044 45 ’ 12 ’ 6’6’ Density =.80 * 1 / (12 + 6) =.044 Occupancy = 80%

31. 31 Arterial Performance Measurement Flow vs. Occupancy: 5 Minute Data

32. 32 Arterial Performance Measurement 5 Minute Speed and Occupancy (at Hamilton)

33. 33 Arterial Performance Measurement Generate Occupancy Map From Detector Data

34. 34 Arterial Performance Measurement AM Peak Speed Map From Detector Data

35. 35 Arterial Performance Measurement Bus Geolocation Data

36. 36 Arterial Performance Measurement Objective  Develop an automated way to report  Speeds  Travel times  Performance measures  Using  Existing ITS signal infrastructure  Automatic Vehicle Locator (AVL) data  Develop an automated way to report  Speeds  Travel times  Performance measures  Using  Existing ITS signal infrastructure  Automatic Vehicle Locator (AVL) data

37. 37 Arterial Performance Measurement 1 Year’s Worth of TriMet Data   92 Bus Line   7,600 Stop Locations   273,469 Runs   140,751,486 Stops   50 Gigabytes of Data   Extensive Network Coverage   Opportunity to Evaluate Multiple Routes on Same Arterial

38. 38 Arterial Performance Measurement Time-Space Diagram Distance Signalized Intersections

39. 39 Arterial Performance Measurement Detector Limited in Space Distance Signalized Intersections

40. 40 Arterial Performance Measurement Bus Limited in Time

41. 41 Arterial Performance Measurement Building on Powell Blvd. Study  Begin with limited signal system data.  Gather archived TriMet AVL data.  Merge two data sources to examine synergies due to data fusion.  Use AVL data to calibrate influence areas from loops.

42. 42 Arterial Performance Measurement Buses Inform Detector Readings – 2/12/07

43. 43 Arterial Performance Measurement Buses Inform Detector Readings – 2/14/07

44. 44 Arterial Performance Measurement Buses Inform Detector Readings – 2/14/07

45. 45 Arterial Performance Measurement Congestion Algorithm 1. 1.Calculate the slope of each bus segment (less dwell time) which is equal to the average bus speed 2. 2.Identify a threshold speed that will be considered congestion 3. 3.Find consecutive segments that experience travel speeds below the threshold ‘congested’ speed 1. 1.Calculate the slope of each bus segment (less dwell time) which is equal to the average bus speed 2. 2.Identify a threshold speed that will be considered congestion 3. 3.Find consecutive segments that experience travel speeds below the threshold ‘congested’ speed

46. 46 Arterial Performance Measurement Midpoint Method Using 5-Minute Data Signalized Intersections

47. 47 Arterial Performance Measurement Adjust Influence Areas Manually Signalized Intersections

48. 48 Arterial Performance Measurement Bus Data Confirms Adjustment Signalized Intersections

49. 49 Arterial Performance Measurement Reveals Gaps in Detection Signalized Intersections

50. 50 Arterial Performance Measurement New Occupancy Map From Combined Sources Signalized Intersections

51. 51 Arterial Performance Measurement An Improvement Over Mid-Point Method Signalized Intersections

52. 52 Arterial Performance Measurement Average Link Travel Times Ground truth

53. 53 Arterial Performance Measurement Obstacles   System Signal Detector   Very Limited Aggregation   Access to Real Time Data   Limited Detection & Spacing   Bus   Access to Real Time Data

54. 54 Arterial Performance Measurement Next Step   System Signal Detector   Cycle level data (Gresham, OR – SCATS)   Bus   TriMet Buses Can Be Probes   Extensive Network Coverage   Opportunity to Evaluate Multiple Routes on Same Arterial

55. 55 Arterial Performance Measurement Bus Frequency

56. 56 Arterial Performance Measurement CTRAN – 10 Second Reporting

57. 57 Arterial Performance Measurement Next Steps: Gresham Burnside Corridor   Good detector density   Highly granular data (cycle-by- cycle)   Probe data available   No direct measurement of occupancy   16’ detectors   No bus data   Good detector density   Highly granular data (cycle-by- cycle)   Probe data available   No direct measurement of occupancy   16’ detectors   No bus data

58. 58 Arterial Performance Measurement Acknowledgements   TransPort Members   FHWA: Nathaniel Price   ODOT: Galen McGill   PSU & OTREC (Local Matching Funds)   City of Portland: Bill Kloos, Willie Rotich   TriMet: David Crout, Steve Callas   JPACT and Oregon Congressional Delegation   ITS Lab: John Chee, Rafael Fernandez   TransPort Members   FHWA: Nathaniel Price   ODOT: Galen McGill   PSU & OTREC (Local Matching Funds)   City of Portland: Bill Kloos, Willie Rotich   TriMet: David Crout, Steve Callas   JPACT and Oregon Congressional Delegation   ITS Lab: John Chee, Rafael Fernandez

59. 59 Arterial Performance Measurement Next Steps: Vancouver Mill Plain Blvd.   Detailed Data Available   Do Not Have Sample Data Yet   Possible Future Project   Detailed Data Available   Do Not Have Sample Data Yet   Possible Future Project