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Activity Modeling of Freight Flows in Washington State: Case Studies of the Resilience of Potato and Diesel Distribution Systems

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Publication Date: 2009
This paper describes the development and use of a network model using publicly available industry data to analyze the resilience of two important Washington state industries. Modeling of freight activity in support of the potato and diesel industry in Washington state demonstrates how individual industries utilize the road network and how they are affected by a transportation disruption. We estimate the potato industry, which relies entirely on trucks for intra-state deliveries, generates about 50 cross-Cascade truck trips per day. Roughly 90 percent of the trucks deliver potatoes from processing facilities on the east side of the state to markets on the west side, while 10 percent carry fresh potatoes from the west to the east for processing. The coupled origins and destinations do not vary unless there is a disruption to the network. The diesel distribution system in Washington state also relies heavily on trucks, but only for the final segment of the logistics chain because both barge transport and pipelines are more cost effective modes. By necessity, trucks deliver from terminals to racks, but there is an established flexibility in these distribution operations as routes and travel distances regularly change because of variations in commodity price at each terminal and the presence of multiple terminals. As a consequence, we demonstrate that the diesel distribution system is much more resilient to roadway disruptions, especially those which occur along the cross-Cascades routes. These examples demonstrate the necessity of understanding industry practice as it relates to analyzing needed infrastructure and operational improvements to reduce economic impacts resulting from transportation disruptions.



Authors: Dr. Anne Goodchild, Sunny Rose, Derik Andreoli, Eric Jessup.
Recommended Citation:
Goodchild, Anne. Sunny Rose, Derik Andreoli, and Eric Jessup. "Activity Modeling of Freight Flows in Washington State: Case Studies of the Resilience of Potato and Diesel Distribution Systems." 

Examining Carrier Categorization in Freight Models

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Publication: Research in Transportation Business & Management
Volume: 11
Pages: 116-122
Publication Date: 2014

Travel demand models are used to aid infrastructure investment and transportation policy decisions. Unfortunately, these models were built primarily to reflect passenger travel and most models in use by public agencies have poorly developed freight components. Freight transportation is an important piece of regional planning, so regional models should be improved to more accurately capture freight traffic. Freight research has yet to fully identify the relationships between truck movements and company characteristics in a manner sufficient to model freight travel behavior. Through analyzing the results of a survey, this paper sheds light on the important transportation characteristics that should be included in freight travel demand models and classifies carriers based on their role in the supply chain. The survey of licensed motor carriers included 33 questions and was conducted in Oregon and Washington. Respondents were asked about their vehicle fleets, locations served, times traveled, time windows, types of deliveries, and commodities. An assessment of how the relationships found can be integrated into existing models is offered.

Authors: Dr. Anne Goodchild, Maura Rowell, Andrea Gagliano
Recommended Citation:
Rowell, Maura, Andrea Gagliano, and Anne Goodchild. Examining Carrier Categorization in Freight Models. Research in Transportation Business & Management 11 (2014): 116-122. 

Estimating Truck Trips with Product Specific Data: A Disruption Case Study in Washington Potatoes

Publication: Transportation Letters: The International Journal of Transportation Research
Volume: 4 (3)
Publication Date: 2013

Currently, knowledge of actual freight flows in the US is insufficient at a level of geographic resolution that permits corridor-level freight transportation analysis and planning. Commodity specific origins, destinations, and routes are typically estimated from four-step models or commodity flow models. At a sub-regional level, both of these families of models are built on important assumptions driven by the limited availability of data. This study was motivated by a desire to determine whether efforts to gather corridor-level freight movement data will bring significant new insights over current approaches to freight transportation modeling. Through a case study of Washington State’s potato and value added potato products industry, we show that significant insight can be gained by collecting commodity-specific truck trip generation and destination data: the approach allows product specific truck trips to be estimated for each roadway link. When considering a network change, the number of affected trips can be identified, and their re-route distance quantified.

Authors: Dr. Anne Goodchild, Derik Andreoli, Eric Jessup
Recommended Citation:
Derik Andreoli, Anne Goodchild & Eric Jessup (2012) Estimating truck trips with product specific data: a disruption case study in Washington potatoes, Transportation Letters, 4:3, 153-166,
Technical Report

Characterizing Oregon’s Supply Chains

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Publication: Oregon Dept. of Transportation, Research Section
Publication Date: 2013

In many regions throughout the world, freight models are used to aid infrastructure investment and policy decisions. Since freight is such an integral part of efficient supply chains, more realistic transportation models can be of greater assistance. Transportation models in general have been moving away from the traditional four-step model into activity-based and supply chain-based models. Personal transportation models take into consideration household demographics and why families travel. Freight research has yet to fully identify the relationships between truck movements and company characteristics, so most freight models use the methodology of personal transportation models, despite situational differences.

In an effort to classify freight companies into groupings with differentiated travel movements, a survey of licensed motor carriers was designed and conducted in Oregon. The survey consisted of 33 questions. Respondents were asked about their vehicle fleets, locations served, times traveled, types of deliveries, and commodities. An analysis of the data revealed clusters of company types that can be distinguished by determining characteristics such as their role in a supply chain, facilities operated, commodity type, and vehicle types. An assessment of how the relationships found can be integrated into state models is also presented.

Authors: Dr. Anne Goodchild, Andrea Gagliano, Maura Rowell
Recommended Citation:
Goodchild, Anne. A. Gagiliano and M. Rowell. 2013. "Characterizing Oregon's Supply Chains." Final Report SPR 739. Oregon Department of Transportation: Research Section and Federal Highway Administration, Salem, OR.
Technical Report

Improved Freight Modeling of Containerized Cargo Shipments between Ocean Port, Handling Facility, and Final Market for Regional Policy and Planning

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Publication: Transportation Northwest (TransNow)
Publication Date: 2008
The proposed research will address an emerging need by local, state and regional transportation planners and policymakers to better understand the transportation characteristics, functions and dynamics of ocean port-to-handling facility and handling facility-to-final market freight movements. The research will also address a gap in the academic literature for freight transportation models that capture underlying economic forces. This research effort will focus on the development and refinement of a regional freight model of urban container movements from the port to a handling facility and beyond. Existing regional transportation planning models and analytical tools have evolved from passenger travel demand models that are ill-suited to fully capture the business decisions and economic influences driving urban freight flows and have been further constrained by access to appropriate freight data. This research activity proposes a modeling approach which will capture the fundamental economic choices individual shippers consider when trading-off the marginal benefits/costs associated with warehouse inventory management/control relative to transportation access and flow while incorporating the primary freight generation activity centers (warehouse/distribution centers) in the Puget Sound region. This work will identify, evaluate and incorporate data for the Puget Sound region recently available from a variety of existing sources. Some data collection may also be necessary. The final product of this research study will be an improved tool to understand current and future freight movements through the Puget Sound region, and a methodology which will expand the current state of knowledge, and may be applied in other regions, both domestic and international. It will allow more in-depth and timely evaluation and analysis of different local/regional transportation policy initiatives such as the impact of migration of the main warehousing region, and development of inland inter-modal port facilities.



Authors: Dr. Anne Goodchild, Kaori Fugisawa, Eric Jessup
Recommended Citation:
Goodchild, Anne V., Eric L. Jessup, and Kaori Fugisawa. Improved Freight Modeling of Containerized Cargo Shipments between Ocean Port, Handling Facility, and Final Market for Regional Policy and Planning. No. TNW2008-08. 2008.
Technical Report

Development and Analysis of a GIS-Based Statewide Freight Data Flow Network

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Publication: Washington State Department of Transportation
Publication Date: 2009
In the face of many risks of disruptions to our transportation system, this research improves WSDOT’s ability to manage the freight transportation system so that it minimizes the economic consequences of transportation disruptions.
Faced with a high probability that major disruptions to the transportation system will
harm the state’s economy, the Washington State Department of Transportation
(WSDOT), in partnership with Transportation Northwest (TransNow) commissioned
researchers at the University of Washington and Washington State University to
undertake freight resiliency research to:
  • Understand how disruptions of the state’s freight corridors change the way
    trucking companies and various freight-dependent industries route goods,
  • Plan to protect freight-dependent sectors that are at high risk from these disruptive
    events, and
  • Prioritize future transportation investments based on the risk of economic loss to
    the state
To accurately predict how companies will route shipments during a disruption,
this research developed the first statewide multimodal freight model for Washington
State. The model is a GIS-based portrayal of the state’s freight highway, arterial, rail,
waterway and intermodal network and can help the state prioritize strategies that protect industries most vulnerable to disruptions.
The report features two case studies showing the model’s capabilities: the potato growing and processing industry was chosen as a representative agricultural sector, and diesel fuel distribution for its importance to all industry sectors. The case studies are found in sections 5.2 and 5.3 in the report and show how the statewide freight model can:
  • Predict how shipments will be re-routed during disruptions, and
  • Analyze the level of resiliency in various industry sectors in Washington State
The two case studies document the fragility of the state’s potato growing and processing
sectors and its dependence on the I-90 corridor, while showing how the state’s diesel
delivery system is highly resilient and isn’t linked to I-90.
As origin-destination data for other freight-dependent sectors is added to the model,
WSDOT will be able to evaluate the impact of freight system disruptions on each of
them. This will improve WSDOT’s ability to develop optimal strategies for highway
closures, and prioritize improvements to the system based on the relative impact of the
This research addressed several technical areas that would need to be resolved by any
organization building a state freight model. First, the researchers had to decide on the
level of spatial and temporal detail to include in the statewide GIS freight model. This
decision has significant consequences for data resolution requirements and results.
Including every road in Washington would have created a cumbersome model with a
large number of links that weren’t used. However, in order to analyze routing during a
disruption all possible connections must exist between origin and destination points in the model. While the team initially included only the core freight network in the model,
ultimately all road links were added to create complete network connectivity.
Second, as state- and corridor-level commodity flow data is practically non-existent, data
collection for the two case studies was resource intensive. Supply chain data is held by
various stakeholders and typically not listed on public websites, and it isn’t organized by
those stakeholders for use in a freight model. In most cases it’s difficult to assure data
quality. The team learned that the most difficult data to obtain is data on spatially or
temporally variable attributes, such as truck location and volume. So they developed a
method to estimate the importance of transportation links without commodity flow data.

Third, the freight model identified the shortest route, based on travel time, between any
origin and destination (O/D) pair in the state, and the shortest travel-time re-route for
each O/D pair after a disruption. The routing logic in the model is based on accepted
algorithms used by Google Maps and MapQuest. Phase III of the state’s freight
resiliency research was funded by WSDOT and will result in improved truck freight
routing logic for the model in 2011.
The two case studies showed how the state’s supply chains use infrastructure differently,
and that some supply chains have built flexibility into their operations and are resilient
while others are not, which leads to very different economic consequences. The results
of these case studies significantly contributed to WSDOT’s understanding of goods
movement and vulnerability to disruptions.
In the future, Washington State will need corridor-level commodity flow data to
implement the research findings and complete the state freight model. In 2009, the
National Cooperative Freight Research Program (NCFRP) funded development of new
methodology to collect and analyze sub-national commodity flow information. This
NCFRP project, funded at $500,000, will be completed in 2010 and provide a mechanism for states to accurately account for corridor-level commodity flows. If funds are available to implement the new methodology in Washington State, the state’s freight
model will use the information to map these existing origin destination commodity flows
onto the freight network, evaluate the number of re-routed commercial vehicles, and their increased reroute distance from any disruption. This will allow WSDOT to develop
prioritized plans for supply chain disruptions, and recommend improvements to the
system based on the economic impact of the disruption.
This report summarizes 1) the results from a thorough review of resilience literature and resilience practices within enterprises and organizations, 2) the development of a GIS-based statewide freight transportation network model, 3) the collection of detailed data regarding two important industries in Washington state, the distribution of potatoes and diesel fuel, and 4) analysis of the response of these industries to specific disruptions to the state transportation network.
The report also includes recommendations for improvements and additions to the GIS model that will further the state’s goals of understanding the relationship between infrastructure availability and economic activity, as well as recommendations for improvements to the statewide freight transportation model so that it can capture additional system complexity.
Authors: Dr. Anne GoodchildDr. Ed McCormack, Eric Jessup, Derik Andreoli, Kelly Pitera, Sunny Rose, Chilan Ta
Recommended Citation:
Goodchild, Anne V., Eric L. Jessup, Edward D. McCormack, Derik Andreoli, S Rose, Chilan Ta and Kelly Pitera. “Development and Analysis of a GIS-Based Statewide Freight Data Flow Network.” (2009).