NCHRP 07-34: Artificial Intelligence for Transportation Systems Management and Operations Applications

Co-PI: Yinhai Wang, Ph.D., P.E., Michael Washkowiak, P.E.

This research aims to guide transportation agencies in developing and implementing next-generation, AI-enabled Decision Support Systems (DSSs) for Transportation Systems Management and Operations (TSMO). TSMO leverages various strategies to optimize existing transportation infrastructure, enhancing efficiency, safety, and air quality. However, traditional DSSs, based on deterministic models, have limitations, such as slow response times and a lack of adaptability to multi-source data. AI-based DSSs address these issues by integrating data from emerging technologies, processing unstructured information, and avoiding human biases in decision-making. The project will create a roadmap for state DOTs and other transportation agencies to deploy AI-enabled DSSs. The guide will include implementation steps, resource needs, and best practices for using AI in various TSMO applications, like traffic signal coordination, incident management, and freeway management. The project also acknowledges the challenges in adopting AI technologies, such as data inconsistency and workforce requirements, and proposes solutions to overcome these barriers.