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FUSING PUBLIC AND PRIVATE TRUCK DATA TO SUPPORT REGIONAL FREIGHT PLANNING AND MODELING

FUSING PUBLIC AND PRIVATE TRUCK DATA TO SUPPORT REGIONAL FREIGHT PLANNING AND MODELING. Chen-Fu Liao Minnesota Traffic Observatory Department of Civil Engineering University of Minnesota Innovations in Freight Demand Modeling and Data A Transportation Research Board SHRP 2 Symposium

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FUSING PUBLIC AND PRIVATE TRUCK DATA TO SUPPORT REGIONAL FREIGHT PLANNING AND MODELING

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  1. FUSING PUBLIC AND PRIVATE TRUCK DATA TO SUPPORT REGIONAL FREIGHT PLANNING AND MODELING • Chen-Fu Liao • Minnesota Traffic Observatory • Department of Civil Engineering • University of Minnesota • Innovations in Freight Demand Modeling and Data • A Transportation Research Board SHRP 2 Symposium • September 14-15, 2010, Washington, DC

  2. Outline • Freight Data Challenges • Objectives • Data Processing and Analysis • Analysis Results • Concluding Remarks and Potential Applications

  3. Freight Data Challenges • Freight data availability • Limited public data • Proprietary nature of private data • Data reliability, quality and cost • Data fusion, integration and management • Transform data into information

  4. Objectives • Use I90/94 as an example to integrate public & private data to analyze freight activity • Compare variations of truck speed and travel time to identify potential freight bottleneck and forecast future freight demand • Identify the needs of regional highway infrastructure improvement to sustain growing freight demand • Generate performance measures to support freight modeling, planning and decision making

  5. Data Summary • FAF2 Data from FHWA • 12 months (May 08 ~ Apr. 09) of Truck AVL/GPS Data from ATRI • Highway Speed Data from MNDOT , Wisconsin DOT and IL State Toll Highway Authority

  6. Average Truck Speed By Location I-94/90 (TWIN CITIES – CHICAGO)

  7. Average Speed (EB) I-90 Toll Highway St. Paul Tomah Madison Chicago

  8. Average Speed (WB) I-90 Toll Highway St. Paul Tomah Madison Chicago

  9. Truck Speed and Volume Variation By Time of Day I-94/90 (Twin Cities – Chicago)

  10. St. Paul, MN EB Mean=46.9, Median=57.7, N=33,610 I-94 at US52 Mean Median WB Mean=46.4, Median=54.6, N=33,788

  11. St. Paul, MN I94 & US52

  12. Performance Index Reliability Measure 95% TT – Avg. TT Buffer Time Index (BTI) = Avg. TT Congestion Measure Peak Travel Time Travel Time Index (TTI) = Free Flow Travel Time

  13. Buffer Time Index (BTI) of Apr. 2009 I-90 Toll Highway 95% TT – Avg. TT BTI = Avg. TT St. Paul Tomah Madison Chicago

  14. Travel Time Index (TTI) of Jan. 2009 Peak Travel Time Travel Time Index (TTI) = Free Flow Travel Time

  15. Trip Destinations Analysis St. Paul Chicago St. Paul Chicago

  16. Truck vs. General Traffic I-90 (S. BELOIT – O’HARE)

  17. I-90 Annual Average Speed (EB) All Traffic Truck Speed Limit 55 MPH Truck Belvidere Marengo Elgin S. Beloit O’Hare General Traffic Speed (Segment Speed) Derived from Illinois Toll Highway Authority Inter-Plaza Travel Time

  18. I-90 Annual Average Speed (WB) All Traffic Truck Speed Limit 55 MPH Truck Belvidere Marengo Elgin S. Beloit O’Hare General Traffic Speed (Segment Speed) Derived from Illinois Toll Highway Authority Inter-Plaza Travel Time

  19. Truck Stops I-94/90 (TWIN CITIES - CHICAGO)

  20. EB Truck Stops (Apr. 2009) Hudson Eau Claire Twin Cities Black River Falls Tomah Mauston Portage Madison Beloit Belvidere Chicago Truck Speed < 5MPH and Travel Distance < 100 meters, N=72,543

  21. WB Truck Stops (Apr. 2009) Hudson Eau Claire Twin Cities Black River Falls Tomah Mauston Portage Madison Beloit Belvidere Chicago Truck Speed < 5MPH and Travel Distance < 100 meters, N=74,405

  22. Truck Stops from TruckMaster

  23. Truck Stop Durations I-94/90 (TWIN CITIES - CHICAGO)

  24. Summary • FPM data can be used to measure performance over time and by location • Truck travel time reliability and level of congestion • Truck volume variation and impact • Performance Index (BTI, TTI) • Truck Destinations • Truck Stops and Rest Durations

  25. Possible Causes of Bottlenecks • Top 30 freight bottlenecks occurred at highway interchange (ATRI Report) • Roadway geometry (grade, sight distance) • Capacity (number of lanes), toll booths • Required lane of travel for trucks • Speed limit and free flow speed • Volume ratio of truck vs. general traffic • Weather and Others

  26. Potential Applications • Truck travel time reliability and impact of congestion on cost of freight • Identify truck stop facility needs • Speed gap between general traffic and truck influenced by traffic volume • Develop national standard to report freight performance measures more regularly • Use derived performance measures to support freight modeling and planning

  27. Acknowledgements • USDOT, FHWA • Minnesota DOT and ATRI • Illinois State Toll Highway Authority • CTS, University of Minnesota (UMN) • Minnesota Traffic Observatory (MTO), Department of Civil Engineering, UMN

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