: Self-driving cars rely on these maps to "see" beyond their immediate sensors, helping them predict lane paths and understand complex signal patterns.
Traditional maps used for navigation (like standard GPS) provide general routing, but offer centimeter-level accuracy. For intersections—the most complex and accident-prone areas of a road network—this involves detailed semantic mapping. IntersectHD
: A tool used by engineers to programmatically build 3D scenes of intersections for automated driving simulations. : Self-driving cars rely on these maps to
: IntersectHD content often focuses on fusing data from multiple sources to overcome "blind spots." This includes LiDAR point clouds for 3D depth, cameras for visual semantic data (like lane markings and signs), and Roadside Units (RSUs) that provide an "overhead" perspective to eliminate vehicle-based occlusions. IntersectHD