This 2024 NHCP research report provides a foundational understanding of ML and its applications and helping to leverage ML for a safer, more efficient, and sustainable transportation future.
NCHRP Research Report 1122: Implementing Machine Learning at State Departments of Transportation: A Guide presents a 10-step roadmap to building agency machine learning (ML) capabilities to (1) educate state departments of transportation (DOTs) on ML applications in transportation; (2) help assess costs, benefits, risks, and limitations of different ML approaches; and (3) assist in building a data-driven organization that can effectively utilize ML. To develop this guide, the research team conducted a review on the state of the art and state of the practice of ML, developed case studies for a variety of data environments, and compiled code examples for major use cases of ML. This publication will be of interest to state DOTs and other stakeholders by providing a foundational understanding of ML and its applications and helping to leverage ML for a safer, more efficient, and sustainable transportation future.
National Academies of Sciences, Engineering, and Medicine. 2024. Implementing Machine Learning at State Departments of Transportation: A Guide. Washington, DC: The National Academies Press. https://doi.org/10.17226/27880.