Advanced Freight Forecasting Models

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Advanced Freight Forecasting Models Prepared for: Innovations in Travel Modeling Workshop Prepared by: Maren Outwater April 30, 2012

Advanced Freight Forecasting Models 3 Types Emerging 1. Supply Chain Models Tend to be National in scope Some examples at State and Regional levels 2. Tour-based Models Tend to be Regional in scope Some examples at State and National levels 3. Hybrid Models Combined supply chain and tour-based models For Regional or Statewide planning purposes, but with a National component

Supply Chain Models

U.S. FAME Framework FAME FREIGHT ACTIVITY MICROSIMULATION ESTIMATOR 4

U.S. Freight Activity Microsimulation Estimator (FAME) 1. All the firms in the study area are recognized and their basic characteristics are identified. 2. Based on each firm s characteristics, the types and amounts of incoming and outgoing goods are determined, and the design of the supply chains is replicated. 3. The shipment sizes are defined based on the acquired information on the firms characteristics and the way that they trade commodities between each other. 4. Shipping decisions such as shipping mode, haul time, shipping cost, warehousing, etc. are made. 5. The impact of the goods movements on transportation network is investigated.

Norway and Sweden National Freight Models Similar (but separate) models for each country Logistics costs for each leg of production-consumption (PC) flow are simulated on a firm-to-firm level Feedback allows logistics choices to impact economic (trade) patterns

Tour-based Models

Tour-based Models Tour-based models include model components for tour generation vehicle-type models trip purpose models time of day models stop location models stop duration models Primarily based on tour characteristics of truck trips and not commodity Focus on truck trips, so they are not multimodal

Tour-based Truck Model Examples Tour-based Truck Model Texas Ohio Calgary Denver Truck Surveys Estimated from Commercial Vehicle Surveys in 2005-2006 Estimated from ODOT surveys in 2003-2004 Estimated from Commercial Vehicle Surveys in 2000 Estimated from DRCOG Surveys in 1998 How Tours are Constructed Daily patterns for trucks, stops chosen then linked Daily patterns for workers, incremental tours Daily tours for workers, incremental tours Daily patterns for trucks, incremental tours

Hybrid Supply Chain and Tour-based Models 10

FHWA Freight Forecasting Framework in Chicago Firm Synthesis Firms by Industry Type and Emp Size By CMAP Zones Supply Chain and Goods Demand Macroeconomic I/O Tables Truck Flows County Business Patterns Shipments for each Buyer- Supplier Pair Annual Commodity Flow Data for US Vehicle/Tour Pattern Choice Distribution Channels Shipments by Distribution Channel (4) Number of Tours Choice Shipment Size and Type National Regional Number of Stops Networks (Line-haul distance, Access, Egress, Cost, Mode, Transfer Facilities) Production Mode and Intermodal Transfers Stop Sequence Stop Duration Empty Trucks Truck Flows Rail Flows Water Flows Air Flows Delivery Time of Day Truck Trip Tables by TOD 11

Firm Synthesis Firms are synthesized for the entire U.S. with a high level of industrial sector detail, and across several employment categories Spatial resolution is more detailed than is used nationally (counties are smaller than FAF zones) 12

Supplier Selection Results The model builds 2.8 million buyer-supplier pairs with one of the pair in the Chicago region The distance distribution of buyer-supplier pairs reflects the spatial distribution of commodity flows 13

Distribution Channel Results Direct distribution channels and channels involving a single type of stop are evenly split and account for almost all of the shipments 14

Shipment Size and Frequency Models Small shipments (<1,000 lb) make up the largest proportion of shipments There is relatively little variation between the commodities: a slightly higher proportion of food shipments are small Annual shipment frequency is calculated by dividing the annual flow for each supplier-buyer pair by the shipment size 15

Mode and Transfer Results Within Chicago movement is all via truck Longer movements include significant intermodal elements, including conversion between (for example) FTL and LTL 16

National Model Sequence 17

Daily Shipments and Warehouse Selection Convert annual to daily shipments Assign shipments to a warehouse/ distribution center Identify warehouse/ distribution center locations from the synthesized business establishments 18

Vehicle Choice/Tour Pattern Results Results produce the majority of tours using smaller 2 axle trucks There are slightly fewer peddling tours than direct tours 19

Number of Tour and Stops The model allocates most shipments to single tour patterns Larger shipments are most likely to be in multiple tour patterns There is a long tail of tours with many stops 20

Stop Duration The model predicts that stops will generally be short on peddling tours and long on direct tours 21

Regional Model Sequence 22

Summary Advanced freight forecasting practice is still emerging Model Type Strengths Weaknesses Supply Chain Representation of complex relationships between suppliers, shippers, transshipment points, and consumers; Good at representing economic drivers and commodity demand systems Tour-Based Good at representing service vehicle movements and local deliveries in urbanized areas Variability in relationships makes generalization difficult; Supporting data difficult to obtain; Missing service-purpose movements Misses inter-city shipments and ties to economic and commodity demand systems Hybrid Combines the best of both model types Comprehensive data difficult to obtain

Maren Outwater Resource Systems Group, Inc maren.outwater@rsginc.com 414-446-5402 www.rsginc.com Colin Smith Resource Systems Group, Inc colin.smith@rsginc.com 802-295-4999 www.rsginc.com