All posts by trac

Transportation Infrastructure Sustainability and Carbon Reduction

WSDOT is combating climate change by working to reduce agency and transportation sector greenhouse gas emissions. One way to accomplish that is to adopt sustainable, low carbon materials and construction methods as standard practice. To do that, it is investigating the use of Environmental Product Declarations and life cycle assessment in construction project procurement (in a concurrent project), and it will develop a sustainable procurement strategy for construction and materials. To assist WSDOT in that goal, UW researchers are working to develop a viable carbon reduction strategy, a greenhouse gas (GHG) inventory procedure, methods for including sustainability in contract documents and specifications, and a method for tracking sustainability commitments throughout the construction process.  This procurement strategy will support WSDOT in purchasing materials and contracting for services that have less negative or more positive effects on the environment and human health.

Principal Investigator: Steve Muench, Civil and Environmental Engineering, UW
Sponsor: WSDOT
WSDOT Technical Monitor: Mohamed Nimeri
WSDOT Project Manager: Mustafa Mohamedali
Scheduled completion: February 2026

Model Deployment of the Virtual Coordination Center for Multimodal Integrated Corridor Management

The Virtual Coordination Center (VCC) is a digital collaborative environment for integrated multimodal transportation corridor management. Under Federal Highway Administration sponsorship, an operational community of state, city, and county agencies—including law enforcement, transit, and transportation departments—developed, deployed, and evaluated a VCC for interagency management of significant traffic incidents in the Seattle urban corridor.

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Analytic Tools for Locating, Sizing, and Evaluating Electric Vehicle Charging Stations

To meet its anticipated growth in electric vehicle adoption, Washington state will need sufficient charging and refueling infrastructure to serve the public. This project reviewed the available analytic tools for planning electric vehicle (EV) charging infrastructure and made recommendations on how to meet legislative requirements for forecasting the needs for zero-emission vehicles and mapping recharging equipment.

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Leading Indicators of Transportation Equity: Equity in Planning

To increase equity in transportation planning, this project sought to identify key performance indicators that can measure the effects of transportation projects on vulnerable populations and to develop a framework for incorporating equity into the Washington State Department of Transportation’s (WSDOT) planning processes for long-range, regional, and corridor planning initiatives.

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Smart Sensor for Snow Avalanche Monitoring, Phase 2

The Washington State Department of Transportation (WSDOT) spends millions of dollars each winter assessing and monitoring the chances of hazardous roadside snow avalanches in Washington’s mountains. For that assessment, dedicated staff hand-dig snow pits, visually evaluate snow conditions, and directly assess avalanche risks to support difficult decisions to open or close roads. The objective of this project is to develop an avalanche sensor for deployment by drone on inaccessible slopes above state roadways that will provide indirect, remote, and real-time information about snow conditions more safely and cost effectively. The research team has already proved the viability of using such sensors to gather temperature, movement, and location data, with a communication range of up to 1,600 feet between them and a base station. In this project, the University of Washington’s STAR Lab will manufacture six to ten sensors for field testing and will place them on a known avalanche path in Snoqualmie Pass. The research team will test the ability of drones to accurately drop and retrieve the sensors. In addition, they will test the communication between the sensors and base station, and they will evaluate the accuracy of the collected snowpack and avalanche information and its value to WSDOT’s avalanche staff.

Principal Investigators:
Yinhai Wang, Civil and Environmental Engineering, UW
Edward McCormack, Civil and Environmental Engineering, UW

Sponsor: WSDOT
WSDOT Technical Monitor: James Morin
WSDOT Project Manager: Doug Brodin
Scheduled completion: February 2025

WSDOT Maintenance Performance Measure Algorithms

WSDOT faces multiple challenges in managing its highway assets. The primary objective of this project was to develop a way to predict the performance of important highway assets such as culverts, barriers/guardrails, traffic signal systems, ditches, slopes, and shoulders. This could help the WSDOT Maintenance Division set performance targets that balance available funds, acceptable performance expectations, and maintenance division priorities, potentially preventing the need for expensive reactive maintenance.

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Data-Driven Assessment of Post-Earthquake Bridge Functionality and Regional Mobility 

Local, state, and federal engineers and emergency managers need reliable estimates of bridge performance after an earthquake so that they can plan pre-event mitigation, post-event response and mobility, and long-term recovery. This project provided improved predictions of the post-earthquake functionality of bridges in Western Washington following a Cascadia Subduction Zone magnitude-9.0 earthquake.

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Preparing for Traffic Signal Operations in a Multimodal Connected and Autonomous Vehicle Environment

Because WSDOT maintains 1,000 signalized intersections throughout the state, it is important for WSDOT to plan for connected and autonomous vehicle (CAV) technology and the information it generates, which may greatly help reduce congestion. However, currently there is no real-time, reliable, and multimodal approach for controlling the timing of signalized intersections in a connected or semi-connected arterial or urban street network. This project was intended to help WSDOT identify the technological issues and requirements of integrating connected vehicle hardware in existing traffic signal systems.

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Internet of Things (IoT) Technologies for Active Transportation Sensing and I2X Applications

Roadway safety can be significantly improved with real-time collection of data on traffic, roadway surface, and environmental conditions and the efficient broadcasting of that information to road users. The UW’s Smart Transportation Applications and Research Laboratory (UW STAR Lab) has developed the Mobile Unit for Sensing Traffic (MUST) device, which is able to collect real-time transportation-related data, such as travel times, speeds, traffic volumes, vehicle types, pedestrian flows, and roadway surface and weather conditions. This project is implementing an AI-based, active transportation sensing (ATS) system based on the MUST device to use for comprehensive traffic scene perception and management. The ATS-MUST system will work as a transportation information center to connect diverse transportation users and elements, including active transportation users, vehicles, the roadway, the environment, and public agencies in support of various infrastructure-to-everything (I2X) applications. The researchers will install it on selected high-risk roadways and intersections to monitor the traffic scene and broadcast useful information to both road users and traffic operations centers. The project will have a statewide impact by providing real-time, multi-modal traffic data and efficient information broadcasting.

Principal Investigator: Yinhai Wang, Department of Civil and Environmental Engineering, UW
Sponsors:
WSDOT
FHWA Statewide Transportation Innovation Council

WSDOT Technical Monitor: Natarajan Janarthanan
WSDOT Project Manager: Doug Brodin
Scheduled completion: September 2024

Cost-Effective, Real-Time Visibility Detection System Based on Internet of Things and Computer Vision Technologies

Roadway safety can be significantly improved with the real-time collection of data on traffic, roadway surface, and environmental conditions and the efficient broadcasting of that information to road users. This project tested a mobile sensing unit and visibility detection system that would collect real-time traffic and environmental data to aid in object detection and tracking.

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