Current Projects

King County Metro Support for ORCA Data Analysis Improvements

Analysis of electronic transit farecard data can provide insight into how travelers use the system and how their behavior changes as both the urban form and transit services change over time. It can be used to answer a variety of policy questions, ranging from the impacts of adopted policies on transit use, to the quantity and quality of trips taken, to the differences in transit services provided to neighborhoods of different income levels to determine the equity of transit services provided throughout the region. The Next Generation One Regional Card for All (NG ORCA) effort includes the development and deployment of a database system called DARe (Data Access and Reporting), which is being used to collect, manage, and store data on the use of ORCA cards and accounts. However, to date transit agency analysts have not fully taken advantage of its reporting function. The UW has an ORCA data reporting system that currently houses data from January 2019 through May 2022. This project is funding continued improvements to the UW system.

Principal Investigator: Ryan Avery, Washington State Transportation Center, UW
Sponsor: King County Metro
Metro Technical Monitor: Melissa Gaughan
Scheduled completion: December 2026

Using LCA to Reduce Embodied Carbon in Pavement Infrastructure at WSDOT

The 2022 FHWA Climate Challenge included a call for state departments of transportation and other public sector stakeholders to explore the use of life cycle assessment (LCA) and environmental product declarations (EPDs) as a standard practice to inform more sustainable pavement material and design selection and to quantify the emissions and impacts of those practices. EPDs are transparent, objective reports that communicate what a product is made of and the life cycle environmental impacts of that product. LCA and EPDs are needed to credibly inventory carbon and determine greenhouse gas emissions. In response to the Climate Challenge, and in collaboration with the Minnesota DOT and Michigan Technological University, this study is working to meet three research objectives: 1) train WSDOT and industry personnel about carbon emissions measurement and reduction, 2) collect life cycle assessment data on WSDOT paving projects, and 3) enable WSDOT to include EPDs in project procurement processes and specifications. Integrating these into WSDOT standard practices will be a critical step in decreasing the carbon footprint of its transportation infrastructure.

Principal Investigators:
Steve Muench, Civil and Environmental Engineering, UW
Kim Schofield, WSDOT
Curt Turgeon, Minnesota DOT
Zhanping You, Michigan Technological University

Subcontractors:
Headlight Inc.
WAP Sustainability Consulting

Sponsors:
FHWA
WSDOT

WSDOT Technical Monitor: Karen Strauss
WSDOT Project Manager: Jon Peterson
Scheduled completion: June 2025

Evaluation of Closed Crossing Indicators

Tactile paving surfaces can be used to convey important information to visually impaired pedestrians about their environment, such as warnings about hazards, guidance for directions, or information about amenities. However, pedestrian crossing closures are still indicated solely by official signs. Currently there are no low maintenance, cost effective, industry standard treatments for tactilely indicating closed pedestrian crossings. WSDOT is testing a proof-of-concept application in a Seattle neighborhood in partnership with Seattle DOT and The Lighthouse for the Blind. For this project, researchers will take advantage of that closed crossing treatment and pilot test location to evaluate such treatments and develop a set of guidelines that WSDOT can use to determine their frequency, their best locations, and the types of surface treatments and materials that should be used.

Principal Investigator: Anat Caspi, Computer Science and Engineering, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Jay Wells
WSDOT Project Manager: Jon Peterson
Scheduled completion: January 2024

Smart and Cooperative Truck Parking Monitoring and Calibration System Empowered by Machine Learning

Current systems that determine parking lot occupancy to inform drivers of available spaces have issues related to calibration and accuracy. In response, this research is creating a truck parking monitoring and calibration system powered by machine learning. Rather than relying on manual calibration, which is labor intensive, inefficient, and difficult to scale up, this research will monitor and calibrate the installed sensing system by creating a data pipeline that includes deep learning and cooperative AI methods. For the developed system, counting data will be obtained by sensors installed at the entrance and exit of a truck parking lot. A separate video surveillance system will collect ground-truth data. Then real-time parking occupancy will be calculated, and error status will be identified by comparing the results with ground-truth records. The cooperative AI calibration component will generate a calibrated occupancy result, confidence rate, sensing system status, and calibration recommendations. The project will also create a live website to show the status of the installed truck parking sensing system and calibration recommendations.

Principal Investigator: Yinhai Wang, Civil and Environmental Engineering, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Matt Neeley
WSDOT Project Manager: David Strich
Scheduled completion: March 2026

Transportation Data Equity Initiative, Phases 2 and 3

Detailed, accurate data about pedestrian spaces, travel environments, and travel services are crucial for trip planners, trip concierges, and mobile wayfinding applications—particularly those that serve the needs of people with disabilities, older adults, and rural populations. However, the necessary data are not collected, stored in standardized formats, or published in ways that navigation apps can access. This project is addressing travel inequities by developing a national pipeline of data intended to help all people navigate sidewalks and transit stations more easily. The project will also extend the national data standards for on-demand transit services (GTFS-Flex), which are used extensively by people with disabilities, for pedestrian paths (OpenSidwalks), and for the mapping of multi-level transit stations (GTFS-Pathways). The project will demonstrate the use of those data and standards in three applications: a multi-modal, accessible travel planner (an extension of AccessMap); Microsoft’s Soundscape application, which helps blind and low-vision people navigate the environment; and an auditory tool called Audium intended to help low-vision individuals navigate transit centers. The project will be deployed in six counties: two each in Maryland, Oregon, and Washington state. In Phase 1 the researchers finalized the plans for building the necessary data infrastructure and developing or improving the software needed for the mobility applications. In phases 2 and 3, they will generate the necessary data, extend the data standards, and build/extend the applications. Field tests will be conducted in years 4 and 5. This contribution to a “new mobility ecosystem” will allow more people to access more destinations on foot and with transit than ever before.

Transportation Data Equity website

Principal Investigators:
Anat Caspi, Computer Science and Engineering, UW

Sponsor: USDOT

Team members:
Cambridge Systematics
City of Bellevue
Gaussian Solutions
Microsoft
Smith-Kettlewell Eye Research Institute
Studio Pacifica
XR Navigation

Participating organizations:
Washington State Department of Transportation
Oregon Department of Transportation
Maryland Department of Transportation

Scheduled completion: December 2025

Truck Parking Information and Management System (TPIMS)

Truck drivers consistently rank parking availability as a top concern. When drivers cannot readily find parking, they are forced to park illegally or continue searching, often violating federal hours-of-service rules. To help commercial drivers plan their trips and maximize the use of available parking, WSDOT, in partnership with the STAR Lab at the University of Washington, is developing and installing a self-learning and optimizing Truck Parking Information and Management System (TPIMS). The UW researchers will support WSDOT in determining site viability and design to prepare for TPIMS development. They will build the server that will host all relevant data and UW analytics algorithms and will integrate it with WSDOT’s data management system. They will enhance the accuracy and reliability of the truck parking availability prediction algorithm based on the results and findings from a pilot project, including fusing real-time data, historical spatial-temporal data, and attributes information into the framework. Finally, the UW team will work with WSDOT to develop an application programming interface to provide third-party access to the resulting occupancy and prediction data. In addition, they will enhance the mobile app developed in the pilot project, such as allowing it to host more parking sites and making it more effective and user friendly to disseminate critical information to truck drivers.

Principal Investigator: Yinhai Wang, Civil and Environmental Engineering, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Matt Neeley
WSDOT Project Manager: Doug Brodin
Scheduled completion: December 2025

Extended Molecular Monitoring for Padden Creek

This study is evaluating the ecological impacts of culvert replacements on Padden Creek near Bellingham, Washington. Padden Creek supports runs of coho and chum salmon and migrating Chinook salmon and steelhead trout. WSDOT began construction in April 2021 to replace two culverts that have slopes that prevent fish passage to improve habitat for migratory species and other wildlife along the 2.7 miles of Padden Creek between Padden Lake and Bellingham Bay. A contractor is replacing the existing concrete box culvert at I-5 with two fish passable bridges and the double concrete box culvert at SR 11 with a 20-foot single span concrete box culvert. To evaluate the impacts of those replacements, UW researchers are sampling the water for DNA at Padden Creek and two control creeks monthly through September 2022. They will develop molecular assays for three to five species that are a priority for WSDOT, such as salmonids, lamprey, and freshwater mussels, by using CRISPR-Cas12a technology. The goal is to hand off these assays to WSDOT and other state agencies so that they may autonomously use these techniques in the future for evaluating these and other waterways.

Principal Investigator: Ryan Kelly, School of Marine & Environmental Affairs, UW
Sponsor: WSDOT

WSDOT Technical Monitors:
Tammy Schmidt
Susan Kanzler

WSDOT Project Manager: Jon Peterson
Scheduled completion: March 2023

WSDOT Developing and Calibrating Fragmental Rockfall Models

Managing rock slopes adjacent to highway infrastructure requires considering possible slope instability and designing mitigation efforts to prevent rockfall damage to the roadway and travelers. When engineers design a slope scaling program, rockfall catchment area, or rockfall barrier, they generally use a rockfall simulation model to predict the potential path and distribution of falling rocks. However, current 2D models tend to significantly overestimate the length of falling blocks’ travel paths, which leads to more expensive and extensive protection than required for slope maintenance. Recent studies have demonstrated that rockfall models built in game engine environments can replicate the observed pathways and fragmentation sizes of rockfall events. The ultimate goal of this pooled fund study, led by WSDOT, is to develop “game-engine”-based 3D rockfall simulation software, based on data from LiDAR or photogrammetry models, that has the potential to more realistically model rockfall fragmentation and large block interaction.

Transportation Pooled Fund details

Principal Investigators:
Joseph Wartman, Civil and Environmental Engineering, UW
Jean Hutchinson, Geological Science and Engineering, Queen’s University
Michael Olsen, Civil and Construction Engineering, Oregon State University

Sponsors: WSDOT
with pooled funds from Alaska, Arizona, California, Colorado, New York, Tennessee, and Texas
WSDOT Technical Monitor: Marc Fish
WSDOT Project Manager: Jon Peterson
Scheduled completion; June 2026

Determination of Laboratory Aging Conditions for Hot Mix Asphalt Cracking Test (IDEAL-CT)

Previous WSDOT studies have indicated that a majority of asphalt pavements fail as a result of cracking first. This is especially concerning with the increased use of recycled asphalt pavement (RAP) and recycled asphalt shingles (RAS), both of which can become severely oxidized and brittle, which can lead to accelerated pavement cracking. WSDOT plans to implement a cracking performance test as a part of hot mix asphalt (HMA) design to improve the cracking performance of asphalt pavement and has selected the IDEAL-CT test. However, before a cracking test can be conducted on an HMA mixture, the HMA samples must be appropriately aged. One of the goals of this project is to develop an aging protocol that will accurately mimic the aging of pavement in the field at the time that cracking occurs—in Washington, typically between three and five years after overlay construction. The researchers also intend to develop a mix design procedure that will improve the cracking resistance of mixes with high percentages of RAP, RAS, and reclaimed asphalt materials. Each year WSDOT spends more than $100 million on asphalt roadways. The results of this study should increase the service lives of asphalt pavements, thereby reducing life cycle costs and also the frequency of traffic disruption during repair.

Principal Investigator: Haifang Wen, Civil and Environmental Engineering, WSU
Sponsor: WSDOT
WSDOT Technical Monitor: Steve Davis
WSDOT Project Manager: Mustafa Mohamedali
Scheduled completion: June 2023

Development of a Specification for Quality Acceptance of Chip Seals Using a Laser Scanner

Chip seals, used for pavement surfacing, rehabilitation, maintenance, and preservation, cover over 7,000 miles of roadway in Washington state. Chip seals (or bituminous surface treatments) involve the application of emulsified asphalt, followed by the spreading of chips and choke stone, compaction, sweeping, and application of a fog seal. The cost of a chip seal project per lane mile is far less than that of hot mix asphalt. However, an inability to accurately measure and control the percentage of chip embedment contributes to unpredictable variation in the performance of chip seal projects. A laser scanner could be used to determine the percentage of chip embedment both quickly and accurately. The device is portable and smaller than a nuclear gauge. However, even though laser scanners have shown great potential, no one has systematically evaluated this tool for use in chip seal construction. In addition, a specification for the required percentage of chip embedment and a test protocol for the laser scanner are needed. This project will draft a specification for the appropriate percentage of chip embedment and will develop a test protocol for the use of a laser scanner in chip seal construction. The results should help prevent premature failure of chip seals and lower pavement life cycle costs.

Principal Investigator: Haifang Wen, Civil and Environmental Engineering, WSU
Sponsor: WSDOT

WSDOT Technical Monitors:
Kevin Littleton
Kim Schofield

WSDOT Project Manager: Jon Peterson
Scheduled completion: December 2023

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