Abstract: Systems and methods are provided for collecting anonymized drive information. A processing device may be configured to receive outputs from one or more sensors; determine at least one motion representation for the host vehicle based on the outputs; receive at least one image representative of an environment of the host vehicle; analyze the at least one image to determine at least one road characteristic associated with a road section; assemble first road segment information relative to a first portion of the road section, wherein the first portion of the road section is separated from a starting point associated with a route traveled by the host vehicle; assemble second road segment information relative to a second portion of the road section; and cause transmission of the first road segment information and the second road segment information to a server for assembly of an autonomous vehicle road navigation model.

Abstract: A system for vehicle navigation may include a processor including a circuitry and a memory. The memory may include instructions that when executed by the circuitry cause the processor to receive navigational information associated with the vehicle including an indicator of a location of the vehicle, and determine target navigational map segments to retrieve from a map database. The map database may include stored navigational map segments each corresponding to a real-world area. The determination of the target navigational map segments may be based on the indicator of vehicle location and on map segment connectivity information associated with the stored navigational map segments. The instructions may also cause the processor to initiate downloading of the target navigational map segments from the map database, and cause the vehicle to navigate along a target trajectory included in one or more of the target navigational map segments downloaded from the map database.

Abstract: A system for vehicle navigation may include a processor including a circuitry and a memory. The memory may include instructions that when executed by the circuitry cause the processor to receive navigational information associated with the vehicle including an indicator of a location of the vehicle, and determine target navigational map segments to retrieve from a map database. The map database may include stored navigational map segments each corresponding to a real-world area. The determination of the target navigational map segments may be based on the indicator of vehicle location and on map segment connectivity information associated with the stored navigational map segments. The instructions may also cause the processor to initiate downloading of the target navigational map segments from the map database, and cause the vehicle to navigate along a target trajectory included in one or more of the target navigational map segments downloaded from the map database.

Abstract: Systems and methods are provided for processing vehicle navigation information. A processing device may be configured to receive navigation information from a plurality of vehicles associated with a common road section; store the navigation information; generate at least a portion of an autonomous vehicle road navigation model for the common road section; and distribute the autonomous vehicle road navigation model to one or more autonomous vehicles. The navigation information from each of the vehicles may include first road segment information relative to a first portion of the common road section, and second road segment information relative to a second portion of the common road section. The second road segment information may include a motion representation for the vehicle and a road characteristic relative to the second portion of the common road section. The second portion may be different from and spatially separated from the first portion of the road section.

Abstract: Systems and methods for harvesting images for vehicle navigation are disclosed. In one implementation, a system includes a processor configured to receive an image having been captured by a camera of a vehicle from an environment of the vehicle during a first time period; during a second time period after the first time period: use a first object model to identify a representation of a first object in the image and localize the image relative to a map database based on the representation of the first object; and store the image in the map database based on the localization; and during a third time period after the second time period, use a second object model to identify a representation of a second object in the image, wherein the second object model was not available to the system during the second time period.

Abstract: A system for vehicle navigation may include a processor including a circuitry and a memory. The memory may include instructions that when executed by the circuitry cause the processor to receive navigational information associated with the vehicle including an indicator of a location of the vehicle, and determine target navigational map segments to retrieve from a map database. The map database may include stored navigational map segments each corresponding to a real-world area. The determination of the target navigational map segments may be based on the indicator of vehicle location and on map segment connectivity information associated with the stored navigational map segments. The instructions may also cause the processor to initiate downloading of the target navigational map segments from the map database, and cause the vehicle to navigate along a target trajectory included in one or more of the target navigational map segments downloaded from the map database.

Abstract: A host vehicle-based feature harvester is disclosed. In one implementation, the feature harvester includes memory and a processor configured to receive a plurality of images captured by a camera onboard the host vehicle, the plurality of images being representative of an environment of the host vehicle; analyze at least one image from the plurality of images to identify a representation of a lane mark; select at least one sample area of the representation of the lane mark, wherein the at least one sample area is associated with an image location of at least a portion of the representation of lane mark; determine a location identifier of the at least one sample area; determine a surface quality indicator associated with the at least one sample area; and cause transmission of the location identifier and the surface quality indicator to an entity remotely-located relative to the host vehicle.

Abstract: Systems and methods are disclosed for mapping lanes for use in vehicle navigation. In one implementation, at least one processing device may be programmed to receive navigational information from a first vehicle and a second vehicle that have navigated along a road segment including a lane split feature; receive at least one image associated with the road segment; determine, from the first navigational information, a first actual trajectory of the first vehicle and a second actual trajectory of the second vehicle; determine a divergence between the first actual trajectory and the second actual trajectory; determine, based on analysis of the at least one image, that the divergence between the first actual trajectory and the second actual trajectory is indicative of the lane split feature; and update a vehicle road navigation model to include a first target trajectory and a second target trajectory that branches from the first target trajectory after the lane split feature.

Abstract: Systems and methods are provided for collecting an nymized drive information. A processing device may be configured to receive outputs from one or more sensors; determine at least, one motion representation for the host vehicle based on the outputs; receive at least one image representative of an environment of the host vehicle; analyze the at least one image to determine at least one road characteristic associated with a road section; assemble first road segment information relative to a first portion of the road section, wherein the first portion of the road section is separated from a starting point associated with a route traveled by the host vehicle; assemble second road segment information relative to a second portion of the road section; and cause transmission of the first road segment information and the second road segment information to a server for assembly of an autonomous vehicle road navigation model.

Abstract: Systems and methods are provided for anonymizing navigation data and generating an autonomous vehicle road navigation model with the anonymized data. A navigation system may receive data relating to a road section from a vehicle. The system may determine one or more motion representations associated with the vehicle and one or more road characteristics associated with the road section. The system may assemble navigation information relative to a first portion and relative to a second portion of the road section. The first and second portions may be spatially separated by a third portion. The system may transmit the navigation information relating to the first and second portions and forego transmitting information relating to the third portion. A server may receive the transmitted navigation information and assemble an autonomous vehicle road navigation model. The server may transmit the navigation model to one or more vehicles for use in autonomous navigation.

Abstract: Systems and methods for automatically generating a navigational map relative to one or more road segments are disclosed. In one implementation at least one processor is programmed to cause collection of first navigational information associated with a first density level; determine, based on sensors of the host vehicle, a location of the host vehicle; determine whether the location is at or within a predetermined distance from a geographical region of interest; cause, based on a determination that the location is at or within the predetermined distance from the geographical region of interest, collection of second navigational information associated with a second density level higher than the first density level; upload from the host vehicle at least one of the collected first or second navigational information; and update the navigational map based on the uploaded first or second navigational information.

Abstract: A system may include at least one processor including circuitry and a memory. The memory may include instructions executable by the circuitry to cause the at least one processor programmed to receive at least one identifier associated with a condition having at least one dynamic characteristic. The at least one identifier may be determined based on acquisition, from a camera associated with a host vehicle, of at least one image representative of an environment of the host vehicle, and analysis of the at least one image to identify the condition in the environment, and analysis of the at least one image to determine the at least one identifier associated with the condition. The at least one processor may also be programmed to update a database record to include the at least one identifier associated with the condition, and distribute the database record to at least one entity.

Abstract: Systems and methods are provided for anonymizing navigation data and generating an autonomous vehicle road navigation model with the anonymized data. A navigation system may receive data relating to a road section from a vehicle. The system may determine one or more motion representations associated with the vehicle and one or more road characteristics associated with the road section. The system may assemble navigation information relative to a first portion and relative to a second portion of the road section. The first and second portions may be spatially separated by a third portion. The system may transmit the navigation information relating to the first and second portions and forego transmitting information relating to the third portion. A server may receive the transmitted navigation information and assemble an autonomous vehicle road navigation model. The server may transmit the navigation model to one or more vehicles for use in autonomous navigation.

Abstract: A navigation system for a vehicle is provided. The system includes at least one processor programmed to: receive from an image capture device one or more images representative of an environment of the vehicle; analyze the one or more images to determine navigational information related to the vehicle; determine based on analysis of at least one of: the one or more images, an output of one or more sensors, or the determined navigational information, whether a fault condition exists relative to the determined navigational information; transmit the navigational information from the vehicle to a server if a fault condition is determined not to exist; and forego transmission of the navigational information from the vehicle to a server if a fault condition is determined to exist.

Abstract: Systems, apparatuses and methods may track air gestures within a bounding box in a field of view (FOV) of a camera. Air gestures made within the bounding box may be translated and mapped to a display screen. Should the hand, or other member making the air gesture, exit the bounds of the bounding box, the box will be dragged along by the member to a new location within the FOV.

Abstract: Systems and methods are provided for anonymizing navigation data and generating an autonomous vehicle road navigation model with the anonymized data. A navigation system may receive data relating to a road section from a vehicle. The system may determine one or more motion representations associated with the vehicle and one or more road characteristics associated with the road section. The system may assemble navigation information relative to a first portion and relative to a second portion of the road section. The first and second portions may be spatially separated by a third portion. The system may transmit the navigation information relating to the first and second portions and forego transmitting information relating to the third portion. A server may receive the transmitted navigation information and assemble an autonomous vehicle road navigation model. The server may transmit the navigation model to one or more vehicles for use in autonomous navigation.

Abstract: A system for hand gesture recognition is described herein. The system includes a display, camera, memory, and processor. The memory that is to store instructions and is communicatively coupled to the camera and the display. The processor is communicatively coupled to the camera, the display, and the memory. When the processor is to execute the instructions, the processor is to estimate one or more motion vectors of an object using a pair of consecutive frames and estimate an average motion vector of the object. The processor is also to obtain a descriptor based on histogram values from a histogram of optical flow (HOOF) of the one or more motion vectors and the average motion vector and classify the descriptor as a gesture.

Abstract: Systems, apparatuses and methods may track air gestures within a bounding box in a field of view (FOV) of a camera. Air gestures made within the bounding box may be translated and mapped to a display screen. Should the hand, or other member making the air gesture, exit the bounds of the bounding box, the box will be dragged along by the member to a new location within the FOV.

Abstract: A system for hand gesture recognition is described herein. The system includes a display, camera, memory, and processor. The memory that is to store instructions and is communicatively coupled to the camera and the display. The processor is communicatively coupled to the camera, the display, and the memory. When the processor is to execute the instructions, the processor is to estimate one or more motion vectors of an object using a pair of consecutive frames and estimate an average motion vector of the object. The processor is also to obtain a descriptor based on histogram values from a histogram of optical flow (HOOF) of the one or more motion vectors and the average motion vector and classify the descriptor as a gesture.