Abstract: Embodiments of the present disclosure relate to encoding of junction area information in map data. In particular, the encoding may include organizing vehicle paths that traverse through a junction area according to path groups and organizing contentions that influence behavior of vehicles traveling along the vehicle paths according to contention groups. In addition, the encoding may include generating direction data structures that associate respective path groups with one or more of the contention groups. In these or other embodiments, the map data that corresponds to the junction area may be updated with direction data structures.

Abstract: In various examples, a network of servers, such as a content delivery network, is used to provide a lightweight approach to hosting and serving HD map data to vehicles. The lightweight approach may allow for modifying various map components, such as tiles, layers, and/or segments. Modifying may include adding, removing, and/or updating the various components. A request to modify a first version of a High definition (HD) map may be received. Map data may be recorded that represents a second version of the HD map. A second request associated with the HD map may be received from a vehicle. Based on this second request, second map data representative of at least a portion of a layer may be identified on at least one server of the network of servers. The second map data may then be transmitted to the vehicle by the network of servers.

Abstract: In various examples, a high definition (HD) map is provided that includes a segmented data structure that allows for selective access to desired road segments and corresponding layers of map data. For example, the HD map may be segmented into a series of tiles that may correspond to a geographic region, and each of the tiles may include any number of road segments corresponding to portions of the geographic region. Each road segment may include a corresponding set of layers—which may include driving layers for use by the ego-machine and/or training layers for generating ground truth data—from the HD map that are associated with the road segment alone. As such, when traversing the environment, an ego-machine may determine one or more road segments within a tile corresponding to a current location, and may selectively download one or more layers for each of the one or more road segments.