In autonomous vehicle development, designs for unstructured, off-road environments can be very different than those designed for structured, on-road applications. A typical on-road deep learning system must focus on identifying cars, pedestrians and traffic signals, and are built to respond to highway markings, such as signage and lane markings. In contrast, off-road autonomous vehicles must be able to detect trees, rocks, abrupt changes in elevation and other obstacles. Active sensors, such as LiDAR, also respond differently to organic materials, like foliage, than to man-made materials, like steel and glass.
The CAVS vehicle proving grounds, located on 55 acres of land adjacent to the CAVS building, provides controlled-access testing capabilities for both autonomous vehicles and vehicle mobility in an off-road environment. The proving grounds feature various terrains, including sand, rocks, tall grass, wooded trails and lowlands. Varying courses provide transition points between different terrain and lighting scenarios. Future improvements to the site include hard-surface test capabilities, such as four-lane roads, entrance and exit ramps, and a general use concrete and asphalt pad.