Improved Signalized Intersection Performance using Computer Vision and Artificial Intelligence

The primary objectives of this research are to: (1) assess the feasibility and accuracy of using computer vision technology for performance evaluation at signalized intersections; (2) provide intersection video footage data captured by drones; (3) use computer vision and artificial intelligence to automatically convert data from video recordings at selected intersections into trajectories of road users; (4) using computer vision and artificial intelligence to count road users, and detect queuing and demand for each approach at selected intersections using drone footage; and (5) develop tools to facilitate Louisiana Department of Transportation (DOTD) traffic engineers in understanding road users' behaviors, evaluating intersection performance measures, and assisting in determining effective measures for improving safety and efficiency at intersections.