Understanding how and when drivers change lanes is key to improving highway traffic flow, safety and autonomous vehicle performance, and a new approach developed at the University of Michigan outperforms current methods using only GPS data.
Up to this point, lange change estimation has been done using on-board cameras or lane-level high-resolution maps that provide geometry, lane markings and lane connections. Both methods are expensive and not always reliable. Cameras fail when the lane lines are faded or occluded and maps are difficult to update at a large scale.
","author_name":"Michigan Engineering "}