Abstract: A system, method and architecture for providing driving recommendations to a vehicle based on network-assisted scanning of a surrounding environment. In one embodiment, the system is operative for receiving environmental data from one or more collection agents, each operating with a plurality of sensors configured to sense data relating to the environment. At least one collection agent is operative in association with the vehicle for providing vehicular condition data and vehicular navigation data. Road condition information and obstacle condition information relating to a road segment, the vehicle is traversing may be obtained. Responsive to the road condition/navigation data, vehicle type and positioning, etc., a routing path over the road segment may be determined. In one configuration, the routing path may be presented via a display (e.g., AR/MR) associated with the vehicle.

Abstract: A system, method and architecture for network-assisted scanning of a surrounding environment. In one example arrangement, the system is operative for receiving one or more pieces of environmental data from a plurality of collection agents, each collection agent operating with a plurality of sensors configured to sense data relating to a respective location area of an environment, wherein the one or more environmental data is received responsive to determining that a portion of the environmental data is necessary for updating a consumption point report. Based on the received data, an updated consumption point report may be generated, which may be transmitted to a data consumption point.

Abstract: A system, method and architecture for network-assisted scanning of a surrounding environment. In one example arrangement, the system is operative for receiving real world object identification and spatial mapping data relative to a plurality of real world scenarios sensed by sensing points, each operating as a collection agent configured to collect environmental data in association with a plurality of sensors. The data may be prioritized responsive to at least one of a determination of RAN resource capacity available to the collection agent, e.g., compute resources, storage resources, radio transmission resources, cost of the transmission capacity available to the collection agent, etc. in view of urgency/relevance of the data. Responsive to prioritizing the environmental data, one or more pieces of the environmental data may be transmitted to a nearest edge compute location and/or a cloud-based datacenter network node.

Abstract: A system, method and architecture for providing driving recommendations to a vehicle based on network-assisted scanning of a surrounding environment. In one embodiment, the system is operative for receiving environmental data from one or more collection agents, each operating with a plurality of sensors configured to sense data relating to the environment. At least one collection agent is operative in association with the vehicle for providing vehicular condition data and vehicular navigation data. Road condition information and obstacle condition information relating to a road segment, the vehicle is traversing may be obtained. Responsive to the road condition/navigation data, vehicle type and positioning, etc., a routing path over the road segment may be determined. In one configuration, the routing path may be presented via a display (e.g., AR/MR) associated with the vehicle.

Abstract: A system, method and architecture for providing highly granular driving recommendations to a vehicle based on network-assisted scanning of a surrounding environment. In one embodiment, the system is operative for receiving environmental data from one or more collection agents, each operating with a plurality of sensors configured to sense data relating to the environment. At least one collection agent is operative in association with the vehicle for providing vehicular condition data and vehicular navigation data. The system is configured to calibrate the vehicle to identify a vehicle type responsive to the vehicular condition/navigation data. Road condition information and obstacle condition information relating to a road segment, the vehicle is traversing may also be obtained. Responsive to the road condition/navigation data, vehicle type and positioning, etc., an optimal racing line path over the road segment may be determined.

Abstract: A system, method and architecture for network-assisted scanning of a surrounding environment. In one example arrangement, the system is operative for receiving real world object identification and spatial mapping data relative to a plurality of real world scenarios sensed by sensing points, each operating as a collection agent configured to collect environmental data in association with a plurality of sensors. The data may be prioritized responsive to at least one of a determination of RAN resource capacity available to the collection agent, e.g., compute resources, storage resources, radio transmission resources, cost of the transmission capacity available to the collection agent, etc. in view of urgency/relevance of the data. Responsive to prioritizing the environmental data, one or more pieces of the environmental data may be transmitted to a nearest edge compute location and/or a cloud-based datacenter network node.

Abstract: A system, method and architecture for providing highly granular driving recommendations to a vehicle based on network-assisted scanning of a surrounding environment. In one embodiment, the system is operative for receiving environmental data from one or more collection agents, each operating with a plurality of sensors configured to sense data relating to the environment. At least one collection agent is operative in association with the vehicle for providing vehicular condition data and vehicular navigation data. The system is configured to calibrate the vehicle to identify a vehicle type responsive to the vehicular condition/navigation data. Road condition information and obstacle condition information relating to a road segment, the vehicle is traversing may also be obtained. Responsive to the road condition/navigation data, vehicle type and positioning, etc., an optimal racing line path over the road segment may be determined.