Nikos Papanikolopoulos, Professor, Computer Science and Engineering
Increased urban sprawl and increased vehicular traffic have resulted in an increased number of traffic fatalities, the majority of which occur near intersections. According to the National Highway Traffic Safety Administration, one out of eight fatalities that occur at an intersection is a pedestrian. An intelligent, real-time system capable of predicting situations leading to accidents or near misses will be very useful for improving the safety of pedestrians as well as vehicles. This project investigated the prediction of such situations using current traffic conditions and computer vision techniques. An intelligent system can gather and analyze such data in a scene (e.g., vehicle and pedestrian positions, trajectories, velocities, etc.) and provide necessary warnings. This work focused on the monitoring aspect of the project. Certain solutions are proposed and issues with the current implementation are highlighted. The cost of the proposed system is low and certain operational characteristics are presented.