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Minnesota Department of Transportation

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Research & Innovation

MnDOT and LRRB research funding awards FY2027

The Minnesota Department of Transportation Research Steering Committee and the Minnesota Local Road Research Board have announced funding awards for the FY2027 academic transportation research Request for Proposals (RFP).

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Primary Category

Need Statement

Proposal Title

Principal Investigator

University

Funding Program

Bridge and Structures

NS-751

Resistances and associated pile lengths of non-displacement piles using static analysis methods

Philippe Kalmogo

University of New Hampshire

RSC

NS-752

Bridge approach roadway embankment improvements

Anand Puppala

Texas A&M University

Joint

U-781

Refining ice loading for Minnesota bridges - Phase II continued data collection

Lauren Linderman

University of Minnesota

RSC

Environmental

KB25-01-1

Developing recommendations for the use of biochar in roadside green infrastructure

Emilie Snell-Rood

University of Minnesota

LRRB

KB25-01-2

Effects of stormwater BMPs on water quality in surface effluent and groundwater during spring snowmelt

Meijun Cai

University of Minnesota

LRRB

KB25-06-1

Utilizing public perceptions to inform successful roadside vegetation planning and management

Michael R. Barnes

University of Minnesota

LRRB

NS-754

Development of inlet protection BMP phasing performance and implementation criteria for all stages of construction

Michael Perez

Auburn University

Joint

NS-757

Characterization, functional longevity, and performance of natural textiles configured as sediment control retention materials

Michael Perez

Auburn University

RSC

Maintenance Operations

NS-753

Modernizing MnDOT's pavement deflection analysis method to accommodate both FWD and TSD data

Syed Haider

Michigan State University

RSC

NS-768

Tools for improving visibility for snow plowing

David Veneziano

Iowa State University

LRRB

NS-770

Assessing the chloride impacts on the pavement structure

Qingli Dai

Michigan Technological University

LRRB

Materials and Construction

KB25-05-1

Robust data driven condition monitoring of pavements based on temperature data

Ketson Roberto Maximiano dos Santos

University of Minnesota

LRRB

NS-755

Review of field produced innovative asphalt concrete mixtures

Zhanping You

Michigan Technological University

RSC

NS-756

Improved calibration process for pavement distress collection and automated processing used by MnDOT

Muhammed Kutay

Michigan State University

RSC

NS-764

Improved seasonal load limits

Mingu Kang

University of St. Thomas

LRRB

NS-766

Effect of using RAP on gravel roads

Jeramy Ashlock

Iowa State University

LRRB

NS-767

Best practice for seal coating & pavement markings with rumble/mumble strips

Zhanping You

Michigan Technological University

LRRB

Multimodal

NS-760

Travel behavior of Minnesota's e-bike users

Kaitlyn Denten

University of Minnesota

LRRB

Policy and Planning

NS-758

Mapping heat vulnerability: A comparative rural-urban study of transportation impacts

Alireza Khani

University of Minnesota

RSC

NS-771

Best practices for using incentives vs. disincentives in contracting

Charles Gurganus

Texas A&M University

LRRB

Traffic and Safety

KB25-03-1

Analysis and risk management of motorcycle, bicycle, and pedestrian crashes in Minnesota

Curtis Craig

University of Minnesota

LRRB

KB25-03-2

Situational awareness alerts for roadside bicycles and pedestrians

Raphael Stern

University of Minnesota

LRRB

KB25-03-3

Creating a real-time road safety evaluation of collision risks based on traffic state estimation

Michael Levin

University of Minnesota

LRRB

KB25-04-1

Portable tool for periodic evaluations of intersection signal timings

Rajesh Rajamani

University of Minnesota

LRRB

NS-759

Effectiveness of stop bar pavement markings in advance of controlled crosswalks

Alyssa Ryan

Michigan State University

LRRB

NS-765

Effectiveness of school zone speed limits as a traffic calming strategy

Peter Savolainen

Michigan State University

LRRB

U-777

Img2Speed: Generative AI and multimodal machine learning for predicting operating speed distributions from roadway design and context

Seongjin Choi

University of Minnesota

RSC

U-782

An analysis of crash data and safety trends in ATVs and UTVs in Minnesota

Natalie Villwock-Witte

Montana State University

Joint

Updated: February 2026