Teaching self-driving cars to predict pedestrian movement

By zeroing in on humans’ gait, body symmetry and foot placement, University of Michigan researchers are teaching self-driving cars to recognize and predict pedestrian movements with greater precision than current technologies. Data collected by vehicles through cameras, LiDAR and GPS allow the researchers to capture video snippets of humans in motion and then recreate them in 3D computer simulation. With that, they’ve created a “biomechanically inspired recurrent neural network” that catalogs human movements…