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Creating a Supply-Chain Methodology

for FreightForecasting in

WisconsinOctober 21, 2013

Jennifer MurrayTraffic Forecasting Section Chief

Wisconsin Department of Transportation

TRB – SHRP2 Symposium: Innovations in Freight Demand Modeling and Data Improvement

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Multimodal Freight Fusion Forecasting Model

Create a statewide freight forecasting framework that integrates travel demand modeling with freight analysis tools, provides performance metrics and analyzes alternative strategies to move freight.

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Objectives for Multimodal Freight Fusion Forecasting Model

Use forecasting model day-to-day Implement national best-practices Visualize the data in one place Align transportation investment with needs Build forward thinking and credibility

with stakeholders

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WISCONSINChicago

Twin CitiesLake Superior

Lake Michigan

Mississip

pi R

iver

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Wisconsin Freight Facilities

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Governor’s Freight Industry Summit

Freight Mobility Action Agenda

Transportation Finance & Policy Commission

Connections 2030: Wisconsin’s Long-range Transportation Plan

Stakeholder Meetings

Freight Industry Partners

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Top Commodity Profiles - Economic Drivers

Tonnage Value Economic

Importance Flows Forecasts

Commodity Tons Mode

Transportation issues associated with each commodity

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Draft Highway Freight Factors on Southeast State

Trunk Highways

Criteria

Thresholds

Weight/Hierarchy

Traffic segments assigned

draft highway “Freight Factor” scores

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Draft Highway Freight Factor Scores

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Continued Partnerships

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Multimodal Freight Fusion Forecasting Model

Freight supply-chain forecasting tool based on traditional statewide 4-step model

Economics of moving freight Business production locations, product types,

availability and general business development timeframes

System performance measures

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Data Improvements Needed Vehicle classification count data Data disaggregation investigation

Commodity information○ Shipping costs○ Commodity weights

Freight supply-chainIntermodal terminal supply-chain dataNew business data

Diesel fuel consumption data Non-highway modes

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Permanent Count Stations (ATRs)Continuous Weight-in-Motion

Continuous ClassContinuous Length

Portable Count StationsShort-term Length

Miscellaneous CountsManual

Centralized Processing

Data Analysis

Data Collection Standards

FHWA/WisDOT StandardsBinning

Data Collection

Traffic Forecast/Projection

Vehicle-Miles of Travel

ModelingMeta Manager

Travel Demand ModelMicrosimulation

Identified Project NeedBudget

Capacity Analysis

Accountability

Expertise in Review and Development of Products

Sufficient Truck Counts

Standard WisDOT Approach Statewide

Data-Driven Concept for FreightFusion Forecasting and Modeling

(as represented by Vehicle Classification Count Data)

Data Refinement / Improvement

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Freight Forecasting with Fusion Concept

Concept continuing to evolve – use the data, contribute to the data – “PLUG-IN”

Flexibility and tailored to needsAir quality modelingMechanistic Empirical Pavement Design

software inputsOversize, over-weight vehicles

Multimodal aspect provides insights Survey businesses for data

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Web-based Interactive Corridor

Mapping Application

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Fusion Model Role

Analysis Transportation project planning

and programming MAP-21 opportunities Last-mile connections Partnering Good stewardship

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Schematic Business Plan for

Fusion Concept Outline long-range goals, expectations Specific uses for the model Guidelines for development, technology,

transportation modes, tool and data updates Budget Performance measures Implementation - “the everyday”

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Thank You!