October 21, 2013 Jennifer Murray Traffic Forecasting Section Chief Wisconsin Department of...
-
Upload
garry-atkinson -
Category
Documents
-
view
214 -
download
0
Transcript of October 21, 2013 Jennifer Murray Traffic Forecasting Section Chief Wisconsin Department of...
1
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
2
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.
3
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
4
WISCONSINChicago
Twin CitiesLake Superior
Lake Michigan
Mississip
pi R
iver
5
Wisconsin Freight Facilities
6
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
7
Top Commodity Profiles - Economic Drivers
Tonnage Value Economic
Importance Flows Forecasts
Commodity Tons Mode
Transportation issues associated with each commodity
8
Draft Highway Freight Factors on Southeast State
Trunk Highways
Criteria
Thresholds
Weight/Hierarchy
Traffic segments assigned
draft highway “Freight Factor” scores
9
Draft Highway Freight Factor Scores
10
Continued Partnerships
11
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
12
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
13
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
14
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
15
Web-based Interactive Corridor
Mapping Application
16
Fusion Model Role
Analysis Transportation project planning
and programming MAP-21 opportunities Last-mile connections Partnering Good stewardship
17
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”
18
Thank You!