university of minnesota fusing public and private truck data to support regional freight planning...
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University of MinnesotaUniversity of Minnesota
FUSING PUBLIC AND PRIVATE TRUCK DATA TO SUPPORT REGIONAL FREIGHT
PLANNING AND MODELING
Chen-Fu LiaoMinnesota Traffic Observatory
Department of Civil EngineeringUniversity of Minnesota
Innovations in Freight Demand Modeling and Data A Transportation Research Board SHRP 2 Symposium
September 14-15, 2010, Washington, DC
University of MinnesotaUniversity of Minnesota
Outline
• Freight Data Challenges• Objectives• Data Processing and Analysis• Analysis Results•Concluding Remarks and Potential Applications
University of MinnesotaUniversity of Minnesota
Freight Data Challenges
Freight data availabilityLimited public dataProprietary nature of private dataData reliability, quality and costData fusion, integration and managementTransform data into information
University of MinnesotaUniversity of Minnesota
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
University of MinnesotaUniversity of Minnesota
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
University of MinnesotaUniversity of Minnesota
I-94/90 (TWIN CITIES – CHICAGO)Average Truck Speed By Location
University of MinnesotaUniversity of Minnesota
MadisonSt. Paul ChicagoTomah
Average Speed (EB)
I-90 Toll Highway
University of MinnesotaUniversity of Minnesota
MadisonSt. Paul ChicagoTomah
Average Speed (WB)
I-90 Toll Highway
University of MinnesotaUniversity of Minnesota
I-94/90 (Twin Cities – Chicago)Truck Speed and Volume Variation By Time of Day
University of MinnesotaUniversity of Minnesota
St. Paul, MN
MeanMedian
WB Mean=46.4, Median=54.6, N=33,788
EB Mean=46.9, Median=57.7, N=33,610
I-94 at US52
University of MinnesotaUniversity of Minnesota
St. Paul, MN
I94 & US52
University of MinnesotaUniversity of Minnesota
95% TT – Avg. TT
Performance Index
Buffer Time Index (BTI) = Avg. TT
Peak Travel TimeTravel Time Index (TTI) =
Free Flow Travel Time
Congestion Measure
Reliability Measure
University of MinnesotaUniversity of Minnesota
Buffer Time Index (BTI) of Apr. 2009
MadisonSt. Paul ChicagoTomah
I-90 Toll Highway
BTI = 95% TT – Avg. TT
Avg. TT
University of MinnesotaUniversity of Minnesota
Travel Time Index (TTI) of Jan. 2009
Peak Travel TimeTravel Time Index (TTI) =
Free Flow Travel Time
University of MinnesotaUniversity of Minnesota
St. Paul ChicagoChicago St. Paul
Trip Destinations Analysis
University of MinnesotaUniversity of Minnesota
I-90 (S. BELOIT – O’HARE)Truck vs. General Traffic
University of MinnesotaUniversity of Minnesota
I-90 Annual Average Speed (EB)
General Traffic Speed (Segment Speed) Derived from Illinois Toll Highway Authority Inter-Plaza Travel Time
S. Beloit O’Hare
All Traffic
Truck
Truck Speed Limit 55 MPH
Belvidere Marengo Elgin
University of MinnesotaUniversity of Minnesota
I-90 Annual Average Speed (WB)
General Traffic Speed (Segment Speed) Derived from Illinois Toll Highway Authority Inter-Plaza Travel Time
S. Beloit O’Hare
All Traffic
Truck
Truck Speed Limit 55 MPH
Belvidere Marengo Elgin
University of MinnesotaUniversity of Minnesota
I-94/90 (TWIN CITIES - CHICAGO)Truck Stops
University of MinnesotaUniversity of Minnesota
EB Truck Stops (Apr. 2009)
Truck Speed < 5MPH and Travel Distance < 100 meters, N=72,543
Twin Cities
Tomah
Madison
Beloit
Chicago
Eau ClaireHudson
Belvidere
Mauston
Black River Falls
Portage
University of MinnesotaUniversity of Minnesota
WB Truck Stops (Apr. 2009)
Truck Speed < 5MPH and Travel Distance < 100 meters, N=74,405
Twin Cities
Tomah
Madison
Beloit
Chicago
Eau ClaireHudson
Belvidere
Mauston
Black River Falls
Portage
University of MinnesotaUniversity of Minnesota
Truck Stops from TruckMaster
University of MinnesotaUniversity of Minnesota
I-94/90 (TWIN CITIES - CHICAGO)Truck Stop Durations
University of MinnesotaUniversity of Minnesota
University of Minnesota
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
University of Minnesota
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
University of Minnesota
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
University of Minnesota
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