1. Comparative Analysis Of Various Travel Time Estimation Algorithms To Ground Truth Data Using Archived Data Christopher M. Monsere Research Assistant Professor Dept of Civil and Environmental Engineering Portland State University Sirisha Kothuri, Kristin Tufte, Robert L. Bertini, School of Urban & Public Affairs Portland State University Incorporating Freight Performance Measures in a Regional Transportation Data Archive Christopher M. Monsere Robert L. Bertini Zachary Horowitz Kristin A. Tufte Department of Civil & Environmental Engineering Intelligent Transportation Systems Laboratory Portland State University NATMEC June 7, 2006 Minneapolis, Minnesota Photo J. Fischer

2. 2 Outline  Brief description of existing archive  Existing performance measurement  Possible freight data sources  Some results  Next steps

3. 3 PORTAL PSU Designated as Regional Archive Center  PSU participates in regional ITS committee—TransPort  PSU designated as regional center for collecting, coordinating and disseminating variable sources of transportation data and derived performance measures.  Bi-state: Oregon and Washington  May expand statewide.

4. 4 PORTAL Architecture Regional ITS Data Sources  98 CCTV Cameras  19 Variable Message Signs (VMS)  485 Inductive Loop Detectors  135 Ramp Meters  Weather data  TriMet Automatic Vehicle Location (AVL) System and Bus Dispatch System (BDS)  Extensive Fiber Optics Network

5. 5 Data Fundamentals What Data Do We Collect?  20-second Intervals Freeway Mainline  Count  Occupancy  Time mean speed  20-second Intervals Freeway On-ramps  Count  Hourly @PDX  Temperature  Precipitation  Every four hours @PDX  Weather descriptor (e.g., clear, mist, light rain, rain, fog, light snow)

6. 6 Data Fundamentals Performance Measures We Compute Segment Length  Vehicle Miles Traveled (VMT) = Count  Segment Length  Travel Time = Segment Length  Speed  Free Flow Travel Time = Segment Length  Free Flow Speed  Vehicle Hours Traveled = Count  Travel Time  Delay = Travel Time − Free Flow Travel Time

7. 7 Data Analysis and Visualization Homepage

8. 8 Data Analysis and Visualization Contour Plots: Speed

9. 9 Data Quality Popup

10. 10 Data Analysis and Visualization Time Series Plots: Volume

11. 11 Data Analysis and Visualization Grouped Data Plots: Speed

12. 12 Performance Reports

13. 13 Monthly Reports

14. 14 Mapping and Spatial Analysis Speed by Month Average Evening Peak Speed (5PM-6PM) July 2005 Dec 2005

15. 15 Mapping and Spatial Analysis Travel Time Reliability Point to Point Off-Peak Travel Time Reliability (I-5 N) Point to Point Peak-Hour Travel Time Reliability (I-5 N)

16. 16 Incident Contour Plot Incident on I-205N at the off ramp for Hwy 212/214. A log truck rear-ended a truck carrying nursery stock; two cars also involved. Incident lasted just over 4 hours. 11/15/2005 Northbound I-205

17. 17 Incident Contour Plot 11/15/2005 Southbound I-205 Incident on I- 205 Southbound. One lane closed.

18. 18 PORTAL Potential Freight Data Sources  Vehicle classification  Continuous - short and long (detector stations)  Fixed classification sites  Weigh-in-motion  Truck monitoring (AVI)  Corridor  Point  Spot vehicle classifications  Port of Portland / METRO / ODOT / WsDOT truck count effort  Other traffic study counts

19. 19 Potential Freight Data Weigh-in-motion and Truck AVI  23 sites  1.5 years of data stored, not yet archived  Researching its usefulness  AVI tag matching project  Merging with other data

20. 20 Potential Freight Data Spot vehicle classifications

21. 21 Potential Freight Data Vehicle classification  Current firmware/software not configured to detect length  PSU MTIP grant to help fix  Instead, uses vehicle classification algorithm for single loop  Wang and Nihan –occupancy, count, speed estimation factor –a number of assumptions

22. 22 Potential Freight Data Vehicle classification

23. 23 Potential Freight Data Vehicle classification  Compare Wang and Nihan estimates  Manual counts  Video processed  Site selection (4)  Existing CCTV and loops in same field of view  Detector quality  Trucks, no congestion  Ability to request PTZ  Manual count  Short ( 39 ft)  Timer based count of video  Autoscope 8.1  RackVision analysis of DVR data

24. 24 Potential Freight Data Vehicle classification

25. 25 Potential Freight Data Vehicle classification

26. 26 Next steps and Concluding Remarks  Continue to explore adding freight data to archive  Vehicle classification  WIM data  AVI tag  Data quality??  Web interface is expanding use of archived data  Increasing awareness of the value of these systems  Provides decision support for transportation officials in the region

27. 27 Acknowledgments  PORTAL Team: Kristin Tufte, James Rucker, Spicer Matthews, Jessica Potter, Sue Ahn, Sirisha Kothuri, Andy Delcambre, Tim Welch, Steve Hansen, Andy Rodriguez, Andrew Byrd  National Science Foundation  Oregon Department of Transportation  City of Portland  TriMet  Portland State University  Oregon Engineering and Technology Industry Council Visit PORTAL online at: http://portal.its.pdx.edu

28. 28 Thank You! Questions?