University District Transportation Technology & Safety Improvements

Updated October 2025

SDOT has completed construction and deployment of the University District Multimodal Integrated Corridor Mobility for All (MICMA) project. This initiative modernized 40 traffic signals and delivered seven new technologies to improve safety, reliability, and mobility for everyone who travels in the University District, whether walking, rolling, biking, taking transit, or driving. 

With the project completed in 2025, the University District now serves as an example for data-driven, multimodal transportation innovations. 

Program Overview

The University District is one of Seattle’s most active travel areas, with the University of Washington campus, two Link light rail stations, two major hospitals, Husky Stadium, and other local destinations drawing tens of thousands of people daily. Prior to the project, many intersections had outdated signal equipment with no communications link to SDOT’s 24/7 Transportation Operations Center. 

The MICMA program replaced this aging infrastructure and introduced smart, connected systems that improve how signals respond to real-time travel conditions.  

The work included: 

• Upgrading 40 signals with new controllers, cabinets, and multimodal detection
• Installing fiber optic communications and closed circuit television (CCTV) cameras for incident response (in compliance with the City’s Surveillance Ordinance)
• Adding accessible pedestrian signals (APS) and ADA-accessible curb ramps
• Testing adaptive, cloud-based, and AI-powered technologies to improve travel safety and efficiency 

Program Components

This project modernized SDOT’s Intelligent Transportation System (ITS) in the University District and piloted seven innovative technologies. Together, they created a foundation for expanding smart mobility tools across Seattle. 

1. Adaptive Signal Control

A peer-to-peer adaptive system was used at six signals along 15th Avenue NE. The system adjusted signal timing based on real-time traffic data to reduce delays and improve travel time reliability for both general traffic and buses on the corridor.

Results:

• Average vehicle travel times improved by up to 11 percent
• Reliability improved by 15 to 20 percent

Outcome:

Based on the results of this pilot, SDOT will continue evaluating additional locations for adaptive control.

2. AI-Based Detection for Pedestrians and Cyclists

The original app-based cyclist detection concept was replaced by AI-powered video detection to passively identify people biking and pedestrians approaching intersections. The system was validated through visual confirmation and data from signal controllers.

Results:

• Passive multimodal detection performed reliably
• Provided accurate data on pedestrian and bicycle activity
• Supported the development of near-miss analytics and safety heat maps

Outcome:

Evaluation completed successfully. SDOT now has an additional tool for detecting pedestrians and people biking as well as experience using near-miss analytics to analyze usage.

3. Pedestrian Surge Management

A system was installed at 15th Ave NE and NE 43rd St to detect large pedestrian surges and adjust crossing times automatically. Hardware installation and integration were completed successfully, but the signal controller could not process multiple simultaneous systems, which prevented a full operational evaluation.

Findings:

• The technology demonstrated the feasibility of detecting pedestrian surges using AI video analytics.
• Insights from the pilot informed updates to SDOT’s Vision Zero pedestrian signal policy, which now prioritizes what is known as “pedestrian recall” citywide. In this mode, pedestrian walk phases automatically display with each vehicle phase. Pedestrians no longer miss a walk signal because they did not push the pedestrian push button to cross the street.

Outcome:

The project advanced SDOT’s understanding of how to manage high pedestrian volumes and directly influenced a citywide policy improvement.

4. Green Wave Emergency Vehicle Priority

A cloud-based emergency vehicle preemption system integrated live dispatch data from the Seattle Fire Department. The system provided coordinated green signals to help clear congestion and improve response time to reach nearby hospitals.

Results:

• Average emergency vehicle response times improved
• Arrivals on green improved by 129 percent
• Seattle Fire Department reported strong operational benefits

Outcome:

A successful pilot of new technology. SDOT will consider expanding Green Wave to other corridors as funding allows.

5. Integrated Corridor Management (ICM)

SDOT implemented real-time data-sharing Application Programming Interfaces (APIs) to connect our arterial management systems with WSDOT’s Virtual Coordination Center (VCC) automating incident and construction data exchange between agencies.

Findings:

WSDOT staff replaced manual coordination such as emails and phone calls with automated data exchanges.
The system strengthened interagency awareness during incidents and demonstrated a successful model for shared regional data services.

Outcome:

The ICM pilot achieved its integration goals and improved coordination between city and state transportation agencies. Future efforts will build on this foundation to enhance joint incident management and response citywide.

6. Automated Traffic Signal Performance Measures (ATSPMs)

SDOT deployed a cloud-based tool that tracks detailed signal performance data.
The system helps engineers assess operations, detect malfunctions, and optimize timing without extensive field work.

Outcome:

A successful pilot of new technology. ATSPMs will be considered for broader deployment based on future needs and available funding to help free up staff resources.

7. Mobility-as-a-Service (MaaS) and Data Portals

The original concept for public kiosks was replaced by improvements to SDOT’s open data platform and internal data management systems. A public-facing online data portal now provides multimodal traffic and collision data in one place.

Results:

• Improved access to data for staff and researchers
• Over 1,000 page views during the first month of launch
• Staff time for responding to data requests reduced by approximately 6 percent
• Accessibility data for sidewalks and curb ramps published using API technology

Outcome:

This process improved SDOT’s understanding of accessibility and increased transparency through open data. Future work will focus on refining standards and expanding public access to transportation data.

Data Privacy and Security

All technologies underwent the City of Seattle’s Privacy Impact Assessment and Surveillance Ordinance reviews. All collected data is anonymized and used only for operational and safety purposes. SDOT remains committed to protecting privacy while advancing transportation innovation.

Looking Ahead

The MICMA project established a foundation for smarter, safer, and more adaptive traffic management citywide. SDOT is now applying these lessons to expand cloud-based systems, integrate AI safety analytics, and strengthen data-sharing tools to support Vision Zero and the Seattle Transportation Plan. These efforts will help Seattle build a transportation system that is safe, sustainable, and connected for everyone.