Abstract: A method for determining a location of a vehicle includes obtaining, by a processor, a plurality of aerial image segment signatures of segments of a region including the vehicle, and a plurality of sensed image signatures associated with the region including the vehicle. The method matches a selected aerial image segment signature segment signatures to a selected sensed image signature. Based on the matching step, the processor generates probabilistic location information regarding the location of the vehicle. The method also includes generating a movement estimate of the vehicles. The movement estimate is generated based on a vehicle location comparison across a plurality of vehicle sensed images, and the plurality of vehicle sensed images are captured at a plurality of time intervals. The method also includes determining the location of the vehicle by combining the movement estimate of the vehicle and the probabilistic location information.

Abstract: A method that is computer implemented and is for air and road based real time driving related decisions, the method includes (i) calculating, by a processor of the vehicle and in real time, a relationship between (a) an air based representation of a lane segment as captured by an air based information and (b) a vehicle based representation of the lane segment as captured by a vehicle based information; wherein the air based representation and the vehicle based representation are located in a same virtual plane; and (ii) determining, by the processor and in real time, a slope value indicative of a slope of the lane, based on the relationship and a mapping between relationship values and lane segment elevation profile values.

Abstract: A method for real time air perception, the method includes continuously obtaining, by a computerized system, aerial image signatures of patches of aerial images in accordance with a determined driving path of the vehicle, such that the patches of aerial images capture at least parts of an environment of the determined driving path for a vehicle; processing, by the computerized system and in real time, the aerial image signatures in accordance with one or more road elements within an environment along the determined driving path of the vehicle; and providing perception results, based on the processing by a classification process running with a neural network in a real time driving of the vehicle, for use in an autonomy-level driving of the vehicle.

Abstract: A method that is computer implemented and is for data layer augmentation, the method includes obtaining, by a processor associated with a vehicle, a data layer associated with road elements of a specified type; obtaining, by a processor associated with a vehicle, localization information regarding a location of the vehicle, wherein the road element information is obtained based on aerial image information within a region of a vehicle and on environmental information sensed by the vehicle; and augmenting the data layer using the localization information, wherein the augmenting of the data layer comprises populating a database with data representing updated road elements location for a group of road elements of the specified type within the region of the vehicle.

Abstract: A method that includes obtaining, by a processor associated with the vehicle, a cross-view based localization of the vehicle that is determined by using air based data in accordance with environmental information sensed by a sensor of the vehicle at the region of the vehicle. Then, obtaining, by accessing a database that is populated to contain a data layer, data layer information regarding locations of a given road setting within the region of the vehicle; obtaining, in real time, ground detection output that is being generated for the given road setting by a perception unit of the vehicle; and providing real-time fine-tuned localization of the vehicle, by continuous alignment of the ground detection output in accordance with the data layer information, for the given road setting.

Abstract: A method for determining a location of a vehicle includes obtaining, by a processor, a plurality of aerial image segment signatures of segments of a region including the vehicle, and a plurality of sensed image signatures associated with the region including the vehicle. The method matches a selected aerial image segment signature segment signatures to a selected sensed image signature. Based on the matching step, the processor generates probabilistic location information regarding the location of the vehicle. The method also includes generating a movement estimate of the vehicles. The movement estimate is generated based on a vehicle location comparison across a plurality of vehicle sensed images, and the plurality of vehicle sensed images are captured at a plurality of time intervals. The method also includes determining the location of the vehicle by combining the movement estimate of the vehicle and the probabilistic location information.

Abstract: A method for using aerial image information, the method includes dynamically determining, by a controller associated with a vehicle, one or more downloading parameters of a downloading of a batch of aerial image signatures; and controlling, by the controller, the downloading of the batch of the aerial image signatures to a memory unit associated with the vehicle for use with vehicle sensed information signatures in a localization of the vehicle.