Development of a portable bicycle/pedestrian monitoring system for safety enhancement

Pedestrians involved in roadway accidents account for nearly 12 percent of all traffic fatalities and 59,000 injuries each year. Most injuries occur when pedestrians attempt to cross roads, and there have been noted differences in accident rates midblock vs. at intersections. Collecting data on pedestrian behavior is a time consuming manual process that is prone to error. This leads to a lack of quality information to guide the proper design of lane markings and traffic signals to enhance pedestrian safety. Researchers at the Georgia Tech Research Institute are developing and testing an automated system that can be rapidly deployed for data collection to support the analysis of pedestrian behavior at intersections and midblock crossings with and without traffic signals. This system will analyze the collected video data to automatically identify and characterize the number of pedestrians and their behavior. It consists of a mobile trailer with four high definition pan-tilt cameras for data collection. The software is custom designed and uses state of the art commercial pedestrian detection algorithms. We will be presenting the system hardware and software design, challenges, and results from the preliminary system testing. Preliminary results indicate the ability to provide representative quantitative data on pedestrian motion data more efficiently than current techniques.