SwRI's Motion Prediction Algorithms Enhance Safety Features for Automated Vehicles

Southwest Research Institute, a leading innovator of machine learning technologies, has developed a motion prediction system that enhances pedestrian detection for automated vehicles. The computer vision tool uses a novel deep learning algorithm to predict motion by observing real-time biomechanical movements with the pelvic area being a key indicator for changes. "For instance, if a pedestrian is walking west, the system can predict if that person will suddenly turn south," said SwRI's Samuel E. Slocum, a senior research analyst who led the internally funded project. "As the push for automated vehicles accelerates, this research offers several important safety features to help protect pedestrians." Recent accidents involving automated vehicles have heightened the call for improved detection of pedestrians and other moving obstacles.