This data set was created to understand the potential for machine learning, computer vision, and HPC to improve the energy efficiency aspects of traffic control by leveraging GRIDSMART traffic cameras as sensors for adaptive traffic control, with a sensitivity to the fuel consumption characteristics of the traffic in the camera’s visual field. GRIDSMART cameras—an existing, fielded commercial product—sense the presence of vehicles at intersections and replace more conventional sensors (such as inductive loops) to issue calls to traffic control.
Filter Projects
Area of Research
A next-generation, digital, communicative “smart” grid will require new operational and planning capabilities and substantial infrastructure investment over several decades to meet the country’s energy goals. To address these challenges, the Department of Energy has established the Grid Modernization Initiative.
The ORNL Database to Enable Face characterization in Driving Studies (DEFADS) is a dataset created by Oak Ridge National Laboratory to help evaluate algorithms used in an analysis of automobile driver behavior.