Aaron Breakstone Master of Urban & Regional Planning Candidate School of Urban Studies & Planning Portland Stat

1. Using Ground Truth Geospatial Data to Validate Advanced Traveler Information Systems Freeway Travel Time Messages2005-2006 TransNow Student Conference, February 9, 2006 Aaron Breakstone Master of Urban & Regional Planning Candidate School of Urban Studies & Planning Portland State University Christopher M. Monsere, Ph.D., P.E. Research Assistant Professor Department of Civil & Environmental Engineering Portland State University Robert L. Bertini, Ph.D., P.E. Associate Professor Department of Civil & Environmental Engineering School of Urban Studies & Planning Portland State University

2. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

3. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

4. Project Goal • Evaluation of Oregon Department of Transportation (ODOT)’s travel time estimating and reporting capabilities

5. Real-time Travel Time Estimates • FHWA policy • Variety of technologies • Inductive loop detectors • Microwave radar • Automatic vehicle tag matching • Video detection • License plate matching • Cell phone matching • Past research • General accuracy in free-flow conditions • Recurring congestion & incidents more challenging

6. Portland ATMS • Freeway surveillance • 485 inductive loop detectors (approximately 175 stations) • Dual loop • Mainline lanes • Upstream of on-ramps • 135 ramp meters • 98 CCTV • ATIS • www.TripCheck.com • Real-time speed map • Static CCTV images • 18 dynamic message signs (DMS) • 3 display travel times

7. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

8. Downtown Portland Study Area • 15 directional freeway links • I-5 (6) • I-205 (3) • I-84 (2) • US-26 (2) • OR-217 (2)

9. Downtown Portland Influence Area 4 • Travel Time 4 (at t = 0) Influence Area 3 • Travel Time 3 (at t = 0) Link Travel Time (TT1 + TT2 + TT3 + TT4) Influence Area 2 • Travel Time 2 (at t = 0) Influence Area 1 • Travel Time 1 Travel Time Calculation

10. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

11. www.portal.its.pdx.edu PORTAL (Portland Regional Transportation Archive Listing) • National ITS Architecture ADUS • Funded by NSF • Direct fiber-optic connection between ODOT and PSU • 20-second data • Occupancy • Volume • Speed • Customized travel time area • Conforms to TMOC

12. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

13. Experimental Design • Analysis of estimates • Plan logical routes • Determine variability • Data collection plan • 5-10 runs required for most links • 4 routes designed • Transitional periods targeted • Groups with 5-7 minute headways • Standard probe vehicle instructions (FHWA)

14. Data Collection • Hardware • Palm handheld computers • Magellan GPS devices • Software • ITS-GPS • Available at www.its.pdx.edu • Individual runs and groups of probe vehicles • Variety of traffic conditions • 45 percent congested • 2 notable incidents

15. Data Collection • 87 probe vehicle runs • 904 minutes (~15 hours) of collection time • 516 miles of data • 12 drivers • 7 days (Wed – Fri)

16. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

17. first point on Link 3 last point on Link 9 last point on Link 2 Probe Vehicle Data • Individual runs downloaded • “run” = several links + extraneous data • Unique ID for each GPS record • Runs plotted on freeway network • Links color-coded • Pertinent data segments extracted

18. Matching Estimates • Nearest 20-second interval • e.g. 9:15:34  9:15:20 • Aggregation • Averages more realistic to operation of system • Average of nearest interval and 1 minute prior • Average of nearest interval and 3 minutes prior

19. Average of previous 3 minutes Probe vs. Estimated Travel Times

20. Results

21. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

22. Conclusions • Estimates reasonably accurate given current system configuration • Many within 20% of probe times • Less so under congested conditions • Incidents produced highest error • Averaging improves accuracy • Detector density and location critical

23. Probe Travel Time: ~11 minutes Estimated Travel Time: ~25.5 minutes Estimated Travel Time: ~9.5 minutes Probe Travel Time: ~14.5 minutes Probe Projection Influence Area Limit Conclusions • Detector density and location critical

24. Conclusions • Incidents difficult to capture Δ = ~7 minutes Δ = ~12.5 minutes

25. Outline • Introduction • Study Area • Archived Data • Data Collection • Data Analysis • Conclusions • Next Steps

26. Next Steps • More data • Targeted conditions • Fill gaps • Incidents • Software/hardware issues • Up-to-date • Different algorithms • Historical data • Data from other detectors

27. Acknowledgements • ODOT • Galen McGill • Stacy Shetler • Dennis Mitchell • Jack Marchant • Hau Hagedorn • Castle Rock Consultants • Dean Deeter • Student Drivers