InTrans / Apr 20, 2026
Happy trails to you: CTRE develops Trail Management Program
CTRE master’s student Tasha Wynne, left, and former CTRE doctoral student Zia Zihan collect trail imagery at Cuyahoga Valley National Park in Ohio
Center for Transportation Research and Education (CTRE) researchers leveraged their pavement management expertise to develop a similar maintenance program for trail systems that will help local agencies throughout the US preserve thousands of miles of paved bike and pedestrian routes.
CTRE Research Scientist Inya Nlenanya and CTRE Director Omar Smadi developed a Trail Management Program at the Institute for Transportation (InTrans), which established standardized metrics for trail surface roughness, typically termed the Bike Roughness Index (BRI), and automated frameworks for surface distress evaluation using deep learning techniques.
The InTrans Trail Management Program has been applied to federally managed trail systems as part of a Federal Highway Administration (FHWA) project, as well as trail routes in central Iowa, northwest Illinois, and throughout Minnesota.
While the Trail Management Program was first developed locally using central Iowa trails, the FHWA effort, which included an assessment of National Park Service trails in locations like Cuyahoga Valley National Park and the George Washington Memorial Parkway, extended the application of the BRI and demonstrated its reliability and utility across diverse trail systems.
“The study also integrated National Park Service and U.S. Forest Service rating systems with quantitative metrics and geospatial tools, highlighting the program’s ability to support more consistent, scalable, and data-driven trail assessments across large networks,” said Smadi.
In parallel with the federal project, the CTRE team also brought their expertise to Minnesota’s Parks and Trails Council to contribute to its 2025 State of the Trails report released earlier this year that assessed the ride quality of the state’s paved trail system and projected future conditions.
The project allowed them to expand the Trail Management Program methodologies and focused on assessing and predicting the deterioration of pedestrian assets such as sidewalks.
“This work applies similar data-driven and modeling approaches to help agencies better understand asset aging, prioritize maintenance, and allocate resources more effectively, demonstrating the broader applicability of the program beyond trail systems,” Nlenanya said.
He said the results of these projects demonstrate that mobile-device-based data collection methods, including accelerometer data and image capture, are effective tools for rapid trail and pedestrian asset condition assessment, and that the BRI is a reliable measure of surface roughness. Additionally, the deep learning model developed as part of these projects successfully identified and quantified different distress types, which can significantly aid in maintenance planning for trail systems.
“The integrated approach we developed supports proactive maintenance strategies, ensuring the safety and quality of recreational trails,” Nlenanya said. “Moreover, the findings from our various projects provide guidelines for optimal data collection, highlighting the potential for these methods to be refined and applied across diverse trail management contexts.”
Additional background about the Iowa-specific project is provided in a previous InTrans news article.