microsimulation of commodity flow in the mississippi valley region
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Microsimulation of Commodity Flow in the Mississippi Valley Region. The Microsimulation Team of the Center for Freight Infrastructure Research and Education September 14, 2010. Idea. Descriptive model - PowerPoint PPT PresentationTRANSCRIPT
Microsimulation of Commodity Flow in the Mississippi Valley Region
The Microsimulation Team of the Center for Freight Infrastructure Research and EducationSeptember 14, 2010
Freight Microsimulation
Idea Descriptive model Exploit multiple freight-related
databases that would ordinarily be difficult to link together
Preserve, as much as possible, the richness and detail, both spatial and economic, of the underlying databases
Focus on 5 key indicator commodities Work mainly at the shipment level Focus on trucks
Freight Microsimulation
Commodities
Chosen from commodities suggested by MVFC states
Greater detail than FAF Commodities with many origins and
destinations in region [SCTG] Corn [02200] Soybeans [03400] Dairy products [all 071xx] Motor vehicle parts [all 364xx] Articles of plastics [all 242xx]
Freight Microsimulation
Databases
Dun & Bradstreet establishments Commodity Flow Survey Census of Agriculture Agricultural surveys Crop maps Benchmark IO table Freight Analysis Framework Ontario Commercial Vehicle Survey Oak Ridge national highway network,
enhanced Others
Freight Microsimulation
Major Steps: Crops Farm synthesis
Crop Harvested acres Location (long/lat) Harvest dates Planting dates On-site storage Truck ownership
Farm shipment generation, by date Number of shipments Size Truck type Destination type (elevator, ethanol, feed lot, etc.) Time of Day
Most of Cedar County, IA
Freight Microsimulation
Iowa Crop Land
Freight Microsimulation
Synthetic Farms for Iowa
Freight Microsimulation
Major Steps: Crops
Elevator shipment generation Similar attributes to farm shipments
Destination choice Shipment distances Establishment employments, types
Freight Microsimulation
SpatialDimensions of Crops Model
Freight Microsimulation
Major Steps: Crops
Some simplifying assumptions, e.g., All farm-based shipments go by truck All exports from elevators do not go by
truck A single farm has just one crop (corn,
soybeans, other) No transshipment points, except elevators. Empties are ignored.
Freight Microsimulation
Major Steps: Manufactured Products Shipments move from establishment to
establishment, perhaps through a transshipment point.
Actual establishments within the region, “super-establishments” outside region One super-establishment for each FAF zone for
each 6-digit NAICS Producing establishments limited to those
which produce the three indicator industrial commodities
Any establishment can be a consumer. No households No empties
Freight Microsimulation
Major Steps: Manufactured Products
Shipment generation Size Mode Need one truck? Needs multiple trucks?
Destination Distance range (CFS) selection Within range, establishment is selected randomly
based on: Fraction of US employment within 6-digit industrial
category Distance within range Industry’s share of commodity purchases from IO
tables
Freight Microsimulation
Major Steps: Manufactured Products
Tour structure selection P-C P-W—C P—W-C P-C-C P-W-W-C P-W—C-C P—W-C-C P-C-C-C
Transshipment point selection Time of day for tour legs
P=producerC=consumerW=transshipment point
Freight Microsimulation
Route Choice and Traffic Assignment
Sensitive to time of day (“dynamic”) Link travel times for route choice FAF zones used only for keeping trips on
correct sides of rivers/borders, otherwise no use of TAZs in the assignment step.
Aggregated to nodal catchment areas (about 43,000)
Multiclass Not capacity restrained Not a traffic microsimulation
Freight Microsimulation
Network
Freight Microsimulation
24-Hour Assignment, All Classes, All Commodities, Late October
Freight Microsimulation
24-Hour Static Assignment, All Classes, All Commodities, Detail
Freight Microsimulation
Traffic Dynamics Trial simulations underway
One hour intervals 60 hours of simulated time to allow shipments to
arrive from west and east coasts E.g., 6 am on Monday to 6 pm on Wednesday
Departure times drawn from uniform probability distributions, with logic to keep leg sequences correct given previous leg departure times and trip times.
Need to account for driver rest periods Need to account for time zones
Very long execution times
Freight Microsimulation
Lessons So Far D&B not perfect but very good, needed
considerable help in the agricultural sectors. High degree of spatial, temporal, economic
detail is achievable Concept is expandable to the full US Concept could be expanded to most, if not
all, commodities Better representation of the supply chain
than found in typical regional models Simulation times are long but not
unreasonable. Limited applicability to long-term forecasts
Freight Microsimulation
The Team Data management: University of
Toledo, Pete Lindquist and staff Data synthesis: University of
Wisconsin—Madison, Jessica Guo and staff
Software development: University of Wisconsin—Milwaukee, Alan Horowitz and staff
Policy: Ernie Wittwer, University of Wisconsin—Madison