This repository contains the code, links to reports, and materials related to the project titled "Current Status of Transportation Data Analytics and Pilot Case Studies Using Artificial Intelligence (AI)" sponsored by the New England Transportation Consortium (NETC).
Data is playing an increasingly crucial role in the decision-making processes of state Departments of Transportation (DOT) for both strategic planning and day-to-day operations. This research provides a comprehensive review of existing and emerging data sources for Transportation Systems Management and Operations (TSMO), evaluating their pros and cons. Interviews with federal and state DOT employees offer insights on future data needs, integration, analysis, archiving, sharing, security, privacy, and workforce development.
Based on the review and interviews, the research offers recommendations on future data needs, emerging data sources, and data processing and analytics. Additionally, three case studies demonstrate the potential of using emerging data and AI technologies to address TSMO needs. These studies utilize advanced radar and thermal camera sensors, along with probe data, to model vehicle speed under various scenarios, examining traffic signs' impact on speed and lane-changing behaviors at work zones, and exploring factors influencing speeding at highway curves and ramps.
New England Transportation Consortium (NETC)
C/O Joh Henault
Maine Department of Transportation
24 Child Street
Augusta, ME 04330