Near-real-time Pedestrian Activity Data Available for Planners Statewide
Item #: 20260073
Item #: 20260073
CONTACTS
Implementing Organization: Planning
Implementation Lead: Kevin Nichol
Development Team:
Utah State University
Patrick Singleton
Amir Rafe
UDOT Research & Innovation
Kevin Nichol, Research Project Manager
UDOT Planning
Neda Kiani
Angelo Papastamos
Heidi Goedhart
UDOT Traffic Management
Mark Taylor
Jamie Mackey
Matt Luker
UDOT Traffic & Safety
Glenn Blackwelder
Travis Evans
UDOT Data Analytics
Scott Jones
Avenue Consultants
Emma Abel
Nuzhat Azra
David Bassett
Daniel Kimball
Shawn Larson
Derek Lowe
Jackson Porter
Article Written By: Kevin Nichol
Innovation Team Coordinator: Quinten Klingonsmith
STATUS
Implementation Date: June 1, 2026
Adoption Status: Fully Implemented
Adoptability Note: How could your team take advantage of this tool to plan safer and more efficient active transportation in your community?
APPLIES TO
Topic: Data Collection, Analysis and Visualization
Organization(s): Central Preconstruction, Data Technology & Analytics, Planning, Region 1, Region 2, Region 3, Region 4, Research and Innovation, Traffic and Safety, Traffic Management Division, Transit and Trails
Job Role(s): Business Analyst, Construction Engineer, Executive Leadership, Program Director, Program Manager, Program Specialist
Tags: active transportation, highway transportation, capital productivity, employee empowerment, political factors, crashes, injuries, economic benefits, expenses, expenditures, value of life, value of time, automation, tracking systems, information technology >> software, networks, ( data visualization ), geographic information systems ( GIS ), intelligent transport systems ( ITS ), data science, design, highway operations, ( traffic operations ), planning, research, pedestrian safety, traffic safety > highway safety, trucking safety, vulnerable road users, public opinion, quality of life, ( connected communities )
Pedestrian count data is highly desirable for planning and prioritizing improvements to active transportation networks, but it is notoriously hard to acquire consistently across the network. Spot counts can be helpful for site-specific information, but they don’t provide a systemwide picture, and they are difficult to expand to scale. Historically, most counts were either manual, using clicker and sheet surveys or video reviews, which are labor intensive, or used automated sensors that would be expensive to implement at the necessary saturation.
The UDOT Planning Division commissioned research through the department’s Research and Innovation Division. Starting in 2018, a team from Utah State’s Department of Civil and Environmental Engineering was selected to find a way to capture pedestrian activity from the records of crosswalk button presses at signalized intersections across the state. The question was, could those activations be extrapolated to model actual pedestrian volumes? Read research report “PEDAT: A Pedestrian Data Platform” (UT-26.10)
In the first phase, researchers found by comparing ped button activations recorded in ATSPM (Automated Traffic Signal Performance Measure system) to manual counts from traffic camera video that they could develop an algorithm that predicts pedestrian volumes from that activation data to a respectable level of accuracy. With this encouraging result, the researchers conducted a second phase to see if the data from signalized intersections could be extrapolated to predict pedestrian volumes at unsignalized intersections without ped button activations, which they found worked well too. In the final phase, the Pedestrian Data platform, or PEDAT, was integrated back into ATSPM.
Planners at UDOT, the metropolitan planning organizations, and consulting firms now have near-real-time access to pedestrian volume estimates that can be used to inform active transportation decision making for access, safety, and system expansion projects.