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

  • 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


Outline FREIGHT PLANNING AND MODELING

  • Freight Data Challenges

  • Objectives

  • Data Processing and Analysis

  • Analysis Results

  • Concluding Remarks and Potential Applications


Freight Data Challenges FREIGHT PLANNING AND MODELING

  • 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


Objectives FREIGHT PLANNING AND MODELING

  • 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


Data Summary FREIGHT PLANNING AND MODELING

  • 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


Average Truck Speed By Location FREIGHT PLANNING AND MODELING

I-94/90 (TWIN CITIES – CHICAGO)


Average Speed (EB) FREIGHT PLANNING AND MODELING

I-90 Toll Highway

St. Paul

Tomah

Madison

Chicago


Average Speed (WB) FREIGHT PLANNING AND MODELING

I-90 Toll Highway

St. Paul

Tomah

Madison

Chicago


Truck Speed and Volume Variation By Time of Day FREIGHT PLANNING AND MODELING

I-94/90 (Twin Cities – Chicago)


St. Paul, MN FREIGHT PLANNING AND MODELING

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


St. Paul, MN FREIGHT PLANNING AND MODELING

I94 & US52


Performance Index FREIGHT PLANNING AND MODELING

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


Buffer Time Index (BTI) of Apr. 2009 FREIGHT PLANNING AND MODELING

I-90 Toll Highway

95% TT – Avg. TT

BTI =

Avg. TT

St. Paul

Tomah

Madison

Chicago


Travel Time Index (TTI) of Jan. 2009 FREIGHT PLANNING AND MODELING

Peak Travel Time

Travel Time Index (TTI) =

Free Flow Travel Time


Trip Destinations Analysis FREIGHT PLANNING AND MODELING

St. Paul

Chicago

St. Paul

Chicago


Truck vs. General Traffic FREIGHT PLANNING AND MODELING

I-90 (S. BELOIT – O’HARE)


I-90 Annual Average Speed (EB) FREIGHT PLANNING AND MODELING

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


I-90 Annual Average Speed (WB) FREIGHT PLANNING AND MODELING

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


Truck Stops FREIGHT PLANNING AND MODELING

I-94/90 (TWIN CITIES - CHICAGO)


EB Truck Stops (Apr. 2009) FREIGHT PLANNING AND MODELING

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


WB Truck Stops (Apr. 2009) FREIGHT PLANNING AND MODELING

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


Truck Stops from FREIGHT PLANNING AND MODELINGTruckMaster


Truck Stop Durations FREIGHT PLANNING AND MODELING

I-94/90 (TWIN CITIES - CHICAGO)


Summary
Summary FREIGHT PLANNING AND MODELING

  • 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


Possible causes of bottlenecks
Possible Causes of Bottlenecks FREIGHT PLANNING AND MODELING

  • 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


Potential applications
Potential Applications FREIGHT PLANNING AND MODELING

  • 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


Acknowledgements
Acknowledgements FREIGHT PLANNING AND MODELING

  • 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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