AI/ML-Driven Safety Analytics

The contract seeks to apply artificial intelligence and machine learning techniques to analyze vehicle safety data with the goal of identifying patterns, forecasting potential risks, and enabling data-informed decisions to enhance road safety. The work involves processing large-scale datasets related to vehicle performance, crash incidents, and operational conditions to develop predictive models that support proactive safety interventions by the National Highway Traffic Safety Administration. The effort is structured as a subcontract under the NAICS code 541511, indicating it is focused on custom computer programming and data analysis services tailored to automotive safety outcomes. Proposals must be submitted by June 23, 2026, and the work will be performed in support of the Department of Transportation’s Office of Acquisition, which is responsible for managing technology-driven initiatives to improve transportation safety. While specific location details are not provided, the project is expected to involve remote or cloud-based data processing and model development, with deliverables tied to actionable insights rather than physical hardware or infrastructure. The project aims to advance the agency’s mission by transforming raw safety data into intelligent systems that can anticipate hazards and contribute to policy and design improvements in the automotive ecosystem.