Using Ground Truth Geospatial Data to Validate Advanced Traveler Information Systems Freeway Travel Time Messages 2005-2006 TransNow Student Conference, February 9, 2006

1
Using Ground Truth Geospatial Data to Validate
Advanced Traveler Information Systems Freeway
Travel Time Messages 2005-2006 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

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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

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Outline

• Introduction
• Study Area
• Archived Data
• Data Collection
• Data Analysis
• Conclusions
• Next Steps

8
Study Area

• 15 directional freeway links
• I-5 (6)
• I-205 (3)
• I-84 (2)
• US-26 (2)
• OR-217 (2)

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Travel Time Calculation
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Outline

• Introduction
• Study Area
• Archived Data
• Data Collection
• Data Analysis
• Conclusions
• Next Steps

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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

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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)

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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

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Data Collection

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

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Outline

• Introduction
• Study Area
• Archived Data
• Data Collection
• Data Analysis
• Conclusions
• Next Steps

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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

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Matching Estimates

• Nearest 20-second interval
• e.g. 91534 ? 91520
• Aggregation
• Averages more realistic to operation of system
• Average of nearest interval and 1 minute prior
• Average of nearest interval and 3 minutes prior

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Probe vs. Estimated Travel Times
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Results
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Outline

• Introduction
• Study Area
• Archived Data
• Data Collection
• Data Analysis
• Conclusions
• Next Steps

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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

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Conclusions

• Detector density and location critical

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Conclusions

• Incidents difficult to capture

? 7 minutes
? 12.5 minutes
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Outline

• Introduction
• Study Area
• Archived Data
• Data Collection
• Data Analysis
• Conclusions
• Next Steps

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Next Steps

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

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Acknowledgements

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