Abstract: For example, an antenna array may include a plurality of antenna elements arranged according to an array arrangement configured to provide a predefined array factor including a main beam between a first angle and a second angle; a first Side-Lobe (SL) region between the first angle and a third angle including one or more first SL peaks below a predefined array factor value; a second SL region between the second angle and a fourth angle including one or more second SL peaks below the predefined array factor value; a third SL region between the third angle and a fifth angle including one or more third SL peaks above the predefined array factor value; and a fourth SL region between the fourth angle and a sixth angle including one or more fourth SL peaks above the predefined array factor value.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a navigation system for a host vehicle may comprise at least one processor. The processor may be programmed to receive from a camera onboard the host vehicle a plurality of captured images representative of an environment of the host vehicle. The processor may provide each of the plurality of captured images to a target object analysis module including at least one trained model configured to generate an output for each of the plurality of captured image. The processor may receive from the target object analysis module the generated output. The processor may further determine at least one navigational action to be taken by the host vehicle based on the output generated by the target object analysis module. The processor may cause the at least one navigational action to be taken by the host vehicle.

Abstract: The present disclosure relates to systems and methods for identifying a wheel slip condition. In one implementation, a processor may receive a plurality of image frames acquired by an image capture device of a vehicle. The processor may also determine based on analysis of the images one or more indicators of a motion of the vehicle; and determine a predicted wheel rotation corresponding to the motion of the vehicle. The processor may further receive sensor outputs indicative of measured wheel rotation associated with a wheel; and compare the predicted wheel rotation to the measured wheel rotation for the wheel. The processor may additionally detect a wheel slip condition wheel based on a discrepancy between the predicted wheel rotation and the measured wheel rotation; and initiate at least one navigational action in response to the detected wheel slip condition associated with the wheel.

Abstract: Systems and methods are provided for collecting anonymized drive information. A processing device may be configured to receive navigation information associated with a common road section including first road segment information relative to a first portion of the common road section, second road segment information relative to a second portion of the common road section, and third road segment information relative to the third portion of the common road section; store the navigation information associated with the common road section; generate at least a portion of an autonomous vehicle road navigation model for the common road section based on the navigation information; and distribute the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road section.

Abstract: Systems and methods are provided for navigating a host vehicle. A navigation system for the host vehicle may include at least one processor programmed to receive images representative of an environment of the host vehicle; analyze at least one of the images to identify navigational state information associated with the host vehicle; determine a plurality of first potential navigational actions for the host vehicle based on the navigational state information; determine respective future states for the plurality of first potential navigational actions; determine a plurality of second potential navigational actions for the host vehicle based on the determined respective future states; select, based on the plurality of second potential navigational actions, one of the plurality of first potential navigational actions; and cause an adjustment of a navigational actuator of the host vehicle to implement the selected one of the plurality of first potential navigational actions.

Abstract: Systems and methods for generating a navigational map are disclosed. In one implementation, a system includes a processor configured to access a navigational map including at least a first map segment representing a first geographical region and a second map segment representing a second geographical region; associate a first control point with a first feature represented in the first map segment; associate a second control point with a second feature represented in the second map segment; associate the first control point with the second control point; use at least one resistance value to warp a location of the first control point from an original position to a warped position based on the association between the first control point and the second control point.

Abstract: Techniques are disclosed to implement a vehicle camera lens cleaning systems that selectively utilize different cleaning modes for the vehicle camera lenses based upon various conditions. The different cleaning modes may be used on a per vehicle camera basis to provide specific types of cleaning to each of the vehicle cameras. The cleaning modes may include the use of air and/or liquid cleaning, which may be provided to each of the vehicle cameras independently.

Abstract: The present disclosure relates to systems and methods for aligning navigation information from a plurality of vehicles. In one implementation, at least one processing device may receive first navigational information from a first vehicle and second navigational information from a second vehicle. The first and second navigational information may be associated with a common road segment. The processor may divide the common road segment into a first road section and a second road section that join at a common point. The processor may then align the first and second navigational information by rotating at least a portion of the first navigational information or the second navigational information relative to the common point. The processor may store the aligned navigational information in association with the common road segment and send the aligned navigational information to vehicles for use in navigating along the common road segment.

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 provided for navigating a host vehicle. A navigation system for the host vehicle may include at least one processor programmed to receive an image representative of an environment of the host vehicle; analyze the image to identify an object in the environment of the host vehicle; determine a location of the host vehicle and a vertical displacement of the object relative to the host vehicle; receive map information including an elevation profile for a road extending away from the location of the host vehicle; determine, based on the vertical displacement of the object and the elevation profile for the road extending away from the location of the host vehicle, a distance from the host vehicle to the object; and determine a navigational action for the host vehicle based on the determined distance.

Abstract: Systems and methods for navigating a host vehicle are disclosed. In one implementation, a system includes a processor configured to receive from a camera onboard the host vehicle an image representative of an environment of the host vehicle. The image is provided to a trained system, which is configured to infer a presence of a curved road segment in the image, wherein the curved road segment is associated with a road on which the host vehicle is traveling. The processor is configured to receive at least one speed value for the host vehicle based on a proximity of the host vehicle to the curved road segment and based on at least one characteristic of the curved road segment represented in the image. The processor is configured to cause the host vehicle to take at least one navigational action based on the determined at least one speed value.

Abstract: A system for navigating a host vehicle relative to a road segment may receive drive information from a vehicle that previously traversed the road segment. Based on at least one road topography indicator, a representation of a first boundary and a second boundary of a lane of travel associated with the road segment may be determined. A left side boundary and a right side boundary of a virtual sleeve associated with the lane of travel may be determined. A vehicle drivable path for the road segment based on the left side boundary and the right side boundary of the virtual sleeve may be generated. The generated vehicle drivable path may be stored in the map. The map may be distributed to at least one host vehicle navigation system.

Abstract: Systems and methods enable detection of occlusion zones while navigating a host vehicle. In one implementation, a navigation system for a host vehicle includes at least one processing device. The at least one processing device is programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify at least one pedestrian occlusion zone in an environment of the host vehicle; and cause a navigational change for the host vehicle based on the identified at least one pedestrian occlusion zone.

Abstract: For example, a polarization rotator may be configured to rotate a polarization of one or more Radio Frequency (RF) signals communicated by one or more antennas via a wireless medium. For example, the polarization rotator may include an input to receive a control signal; and a plurality of polarization-rotator cells switchable between a plurality of predefined states, for example, based on the control signal. For example, the plurality of predefined states may include a no-rotation state and a rotation state. For example, the plurality of polarization-rotator cells may be configured to transfer the RF signals between the one or more antennas and the wireless medium at the no-rotation state, and to transfer the RF signals with a predefined polarization rotation applied to the RF signals at the rotation state.

Abstract: A system for navigating a host vehicle receives a plurality of captured images acquired by at least one camera onboard the host vehicle. The system determines an actual velocity vector for the host vehicle based on the plurality of captured images and compares the actual velocity vector to an expected velocity vector. The system also determines a lateral slip angle based on an observed angular difference between the actual velocity vector and the expected velocity vector. The system causes the host vehicle navigation system to take at least one action based on the determined lateral slip angle.

Abstract: For example, a processor may be configured to identify one or more sets of virtual antenna values corresponding to one or more sets of overlapping virtual antennas, respectively. For example, a set of virtual antenna values corresponding to a set of overlapping virtual antennas may include a first virtual antenna value corresponding to a first virtual antenna, and a second virtual antenna value corresponding to a second virtual antenna. For example, the first virtual antenna may be based on a combination of a first Transmit (Tx) antenna and a first Receive (Rx) antenna, and the second virtual antenna may be based on a combination of a second Tx antenna and a second Rx antenna. For example, the processor may determine a plurality of adjusted virtual antenna values by adjusting a plurality of second-Tx-based virtual antenna values based on the one or more sets of virtual antenna values.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Abstract: A computer-implemented method for navigating a host vehicle includes receiving an image frame from an image capture device, the image frame representing an environment of the host vehicle and including a representation of a target vehicle; analyzing the image frame to determine a sparse representation of a portion of the image frame; providing the sparse representation to an object detection network; receiving an identifier of a candidate region identified by the object detection network; based on the identifier, extracting the candidate region from the image frame; providing the candidate region to an open door detection network; determining a navigational action for the host vehicle in response to an indication from the open door detection network that the candidate region includes a representation of a door of the target vehicle in an open condition; and causing an actuator associated with the host vehicle to implement the navigational action.

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: Systems and methods are provided for vehicle navigation. In one implementation, a navigation system for a host vehicle includes at least one processor programmed to: receive, from a camera of the host vehicle, one or more images captured from an environment of the host vehicle; analyze the one or more images to detect an indicator of an intersection; determine, based on output received from at least one sensor of the host vehicle, a stopping location of the host vehicle relative to the detected intersection; analyze the one or more images to determine an indicator of whether one or more other vehicles are in front of the host vehicle; and send the stopping location of the host vehicle and the indicator of whether one or more other vehicles are in front of the host vehicle to a server for use in updating a road navigation model.