Abstract: In one embodiment, a method of generating a trajectory of a vehicle on a map includes receiving map data of the map, wherein the map data includes a first road and a second road. The method further includes receiving odometry data from one or more sensors of the vehicle, the odometry data having an odometry uncertainty associated therewith, and receiving a plurality of vehicle location signals, each vehicle location signal having a location uncertainty associated therewith. The method also includes generating the trajectory of the vehicle on the first road or the second road of the map by providing as input to an optimizer the odometry uncertainty and the location uncertainty of the plurality of vehicle location signals as constraints.

Abstract: In one embodiment, a method of localizing a vehicle on a map includes receiving map data having a first road with a first number of lanes and a second road with a second number of lanes, receiving sensor data from one or more sensors of the vehicle, and receiving a vehicle localization signal. The method further includes generating, from the sensor data, a local map having a local map number of lanes for vehicle localization signal, and localizing the vehicle on the first road or the second road based at least in part on the local map number of lanes for the vehicle localization signal, the first number of lanes, and the second number of lanes.

Abstract: Systems and methods for generating three-dimensional meshes that represent road surfaces of a road network are disclosed herein. In one example, a system includes a processor and a memory having instructions that, when executed by the processor, cause the processor to generate a three-dimensional mesh representing road surfaces of a road network using a connection graph, a separation graph, and drivable surface polygons representing drivable surfaces of the road and generate a road graph for an electronic map based on the three-dimensional mesh, wherein the road graph is a digital representation of a topology of a road network.

Abstract: Systems and methods for generating drivable surface polygons for electronic map generation are described herein. In one example, a system includes a processor and a memory in communication with the processor having instructions that, when executed by the processor, cause the processor to generate drivable surface polygons that represent a drivable surface of a road using key point detections and a vehicle trace and generate an electronic map based on the drivable surface polygons.

Abstract: Systems and methods are disclosed herein for performing unstructured lane estimation. In one example, unstructured lane estimation involves the steps of receiving an overhead representation of a region and a rasterized trace generated from sensors of a vehicle traveling in the region and outputting, using a machine learning model, probabilities that neighboring pixels of pixels forming the rasterized trace is part of a lane based on the overhead representation and the rasterized trace.

Abstract: Systems and methods are disclosed herein for performing unstructured lane estimation. In one example, unstructured lane estimation involves the steps of receiving an overhead representation of a region and a rasterized trace generated from sensors of a vehicle traveling in the region and outputting, using a machine learning model, probabilities that neighboring pixels of pixels forming the rasterized trace is part of a lane based on the overhead representation and the rasterized trace.