Artificial Intelligence Transportation Systems Management and Operations Data initiative

The United States Department of Transportation (USDOT) / Federal Highway Administration (FHWA) is conducting market research to determine if there are any small businesses, academic institutions, etc., capable of developing Artificial Intelligence (AI) Transportation Systems Management and Operations (TSMO) Data initiative. The goal of this project is to conduct a comprehensive TSMO data gap assessment and produce priority recommendations that document the existing state of practice for TSMO data. The project will explore innovative data-centric AI approaches to enhance the efficiency of data discovery and processing and recommend data benchmarking strategies, with the aim to support responsible AI models' development and deployment tailored to specific TSMO functions and needs. • The project will define the public sector's current state of practice in collecting, managing, integrating, and using TSMO data, focusing on AI models currently applied in TSMO programs and projects. • The project will identify data, metadata, and interoperability requirements for AI-enabled TSMO use cases such as incident prediction, arterial performance analytics, freight corridor management, work zone risk detection, and winter maintenance optimization. • The project will evaluate data barriers and risks that limit public agencies in implementing AI-driven TSMO applications, including issues related to data quality, governance, privacy, access, lineage, and TEVV readiness. • The project will develop innovative approaches aiming to address these gaps and barriers for prioritized TSMO use cases.