Project Details

Abstract

The proposed project seeks to transform national transportation asset datasets into actionable intelligence for preservation planning. Recognizing the fragmentation between roadway and bridge performance data within the Highway Performance Monitoring System (HPMS) and National Bridge Inventory (NBI), the project introduces an AI-driven framework to systematically connect these datasets and develop a unified risk index. The study will first conduct comprehensive literature and data reviews to identify gaps in cross-asset analysis and assess data quality through spatial joins and validation of key attributes such as average daily traffic (ADT). Using descriptive, prescriptive, and predictive analytics, the research will examine relationships among international roughness index (IRI), bridge condition ratings, and traffic loading to uncover deterioration trends and key predictive features. The research will apply advanced machine learning models to forecast performance and support prioritization under budget constraints. The resulting risk index will provide transportation agencies with an objective method to rank preservation needs. This result will enhance Transportation Asset Management Plans (TAMPs) and ensure data-driven resource allocation. Expected outcomes include a validated analytic framework, cross-asset integration methods, predictive deterioration models, and interactive visualization dashboards to aid decision-making. The project directly supports USDOT’s strategic goals of economic strength and global competitiveness by improving asset reliability, minimizing disruptions to freight and passenger mobility, and extending infrastructure service life. Educationally, it will train at least one doctoral student in advanced analytics and risk-based asset management. The research will also integrate the methods and results into graduate coursework and research. Technology transfer activities will disseminate results through academic publications, conference presentations, outreach products, and online tools. Stakeholder engagement will ensure practical adoption. Overall, this project aims to deliver a replicable, scalable decision-support tool to strengthen national transportation resilience and investment efficiency.

Project Word Files