University of Washington

18 Pacifi c Northwest Transportation Consortium An In-Depth Study to Categorize Pacifi c Northwest Highway Project Types as a Way to Enhance Future Investigative Study on Contract Administration Practices and Performance • PI: George Okere (WSU) The objective of this research is to develop a classifi cation system for project types using data from Pacifi c Northwest DOTs on projects that are completed, active and awaiting execution. The classifi cation system will be based on several dimensions such as type of system, geographical location, controlling scope of work, level of complexity, contractual constraint, project delivery method, and other set parameters. Such standardization could improve validity of research fi ndings, and deeply enhance research and practice on highway projects within the Pacifi c Northwest and the entire U.S. This is an in-depth analysis of Pacifi c Northwest highway projects within the last fi ve years. Working with data gathered from the state DOTs, a criteria will be developed for categorizing different project types based on a set of dimensions and measures. A fi nal review will be conducted by the state DOTs to validate and verify that projects are correctly mapped, and if necessary, refi ne the grouping to accommodate gaps. Washington State School Walk Score • PI: Anne Vernez-Moudon (UW) We have developed and tested an approach to the School Walk Score as part of the National Institute of Health Walking School Bus project (Walking School Bus R01CA163146, J. Mendoza, PI; in collaboration with TAMU, C. Lee, PI). We will be working closely with Ms. Charlotte Claybrooke, WSDOT Safe Routes to School Coordinator, and other stakeholders to produce walkability scores for schools in Washington State. The methods will be open-sourced so others can apply them as needed. How Does Charging Network Design Affect Electric Vehicle Adoption? • PI: Don MacKenzie (UW) The goal of this project is to enable investments in electric vehicle (EV) charging infrastructure that most effectively increase consumer demand for EVs. We will use a data-driven approach to understand how charging infrastructure system attributes (station locations, density, type, etc.) affect demand for EVs across regions with diverse mobility needs. This knowledge will help state and local offi cials to ensure that the benefi ts of EVs, including their lower per-mile costs and lighter environmental impacts, are available to all residents in the Northwest. We plan to use region-level data from across the US to identify how changes in different types of public charging stations (Level 2, DC fast charging) lead to changes in the sales of different types of electric vehicles – battery electric and plug-in hybrid vehicles – in future periods. Vehicle sales data at the metropolitan statistical area (MSA) level will be purchased from IHS Inc., and the Department of Energy's Alternative Fuels Data Center is the source of charging infrastructure data. The results of this work will be incorporated into a WSDOT-supported effort to develop an agent-based simulation of statewide electric vehicle travel and charging demand for Washington State.

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