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1 TRB 88 th Annual Meeting January 12, 2009 – TRB 88 th Annual Meeting Mathew Berkow, Robert L. Bertini, Christopher Monsere, Michael Wolfe, Portland State University Peter J.V. Koonce, Kittelson & Associates, Inc. Prototype for Data Fusion Using Stationary and Mobile Data Sources for Improved Arterial Performance Measurement
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2 TRB 88 th Annual Meeting 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
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3 TRB 88 th Annual Meeting Presentation Outline 1.Previous Research & Ground Truth 2.Limitations of Each Data Source 3.Buses Identify Congestion 4.Map Derived from Two Sources 5.Next Steps 1.Previous Research & Ground Truth 2.Limitations of Each Data Source 3.Buses Identify Congestion 4.Map Derived from Two Sources 5.Next Steps
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4 TRB 88 th Annual Meeting Inspiration – Signal System Data Only
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5 TRB 88 th Annual Meeting DD Portland’s Detection Infrastructure Data Aggregation Count Station - 5 min Other Detector - 15 min 7 Day Sample
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6 TRB 88 th Annual Meeting Case Study: Barbur Blvd. Speed Map Sheridan Hooker Hamilton 3rd Terwilliger Bertha 19th I-5 Off-ramp 30th Park & Ride N 4.5 miles long 5 signal detectors
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7 TRB 88 th Annual Meeting 1 Year’s Worth of TriMet Data Bus Lines 92 Stop Locations 7,600 Runs 273,469 Stops 140,751,486 Gigabytes of Data 50
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8 TRB 88 th Annual Meeting Previous Research & Ground Truth
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9 TRB 88 th Annual Meeting TriMet Archived AVL 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
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10 TRB 88 th Annual Meeting Powell Blvd. Corridor Study
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11 TRB 88 th Annual Meeting Previous Results Maximum Speed Method correlated with vehicular travel times. Test vehicle travel times were between 1.24 and 1.29 times the pseudo bus travel times. In reverse, test vehicle speeds were between 0.78 and 0.81 times the pseudo bus speeds. Maximum Speed Method correlated with vehicular travel times. Test vehicle travel times were between 1.24 and 1.29 times the pseudo bus travel times. In reverse, test vehicle speeds were between 0.78 and 0.81 times the pseudo bus speeds.
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12 TRB 88 th Annual Meeting Limitations of Each Data Source
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13 TRB 88 th Annual Meeting Time-Space Diagram Distance Signalized Intersections
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14 TRB 88 th Annual Meeting Detector Limited in Space Distance Signalized Intersections
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15 TRB 88 th Annual Meeting Inspiration – Bus AVL System Data Only
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16 TRB 88 th Annual Meeting Bus Limited in Time
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17 TRB 88 th Annual Meeting 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.
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18 TRB 88 th Annual Meeting Buses Identify Congestion
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19 TRB 88 th Annual Meeting Buses Inform Detector Readings – 2/12/07
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20 TRB 88 th Annual Meeting Buses Inform Detector Readings – 2/13/07
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21 TRB 88 th Annual Meeting Buses Inform Detector Readings – 2/14/07
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22 TRB 88 th Annual Meeting Buses Inform Detector Readings – 2/14/07
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23 TRB 88 th Annual Meeting 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
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24 TRB 88 th Annual Meeting Map from Derived from Two Sources
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25 TRB 88 th Annual Meeting Midpoint Method Using 5-Minute Data Signalized Intersections
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26 TRB 88 th Annual Meeting Adjust Influence Areas Manually Signalized Intersections
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27 TRB 88 th Annual Meeting Bus Data Confirms Adjustment Signalized Intersections
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28 TRB 88 th Annual Meeting Reveals Gaps in Detection Signalized Intersections
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29 TRB 88 th Annual Meeting New Occupancy Map From Combined Sources Signalized Intersections
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30 TRB 88 th Annual Meeting An Improvement Over Mid-Point Method Signalized Intersections
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31 TRB 88 th Annual Meeting Average Link Travel Times Ground truth
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32 TRB 88 th Annual Meeting Next Steps
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33 TRB 88 th Annual Meeting Obstacles System Signal Detector Very Limited Aggregation Access to Real Time Data Limited Detection & Spacing Bus Access to Real Time Data
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34 TRB 88 th Annual Meeting 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
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35 TRB 88 th Annual Meeting Bus Frequency
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36 TRB 88 th Annual Meeting CTRAN – 10 Second Reporting
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37 TRB 88 th Annual Meeting 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
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38 TRB 88 th Annual Meeting Thank You! www.its.pdx.edu
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