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.

Abstract: A system for navigating a host vehicle relative to a road segment may receive a captured image acquired by a camera onboard the host vehicle, wherein the captured image includes representations of at least a first object and a second object present in an environment of the host vehicle; provide the captured image to a trained model configured to receive the captured image as input, apply large language model functionality to establish a semantic constraint between the first object and the second object, and generate an output that identifies the semantic constraint between the first object and the second object; determine, based on the semantic constraint between the first object and the second object, at least one navigational action for the host vehicle; and cause the host vehicle to implement the at least one navigational action.

Abstract: A system may receive, from a map associated with a road segment, at least one indicator of a lane of travel associated with the road segment, location information associated with the lane of travel, an identifier of a road element associated with the road segment, and location information associated with the road element; generate a graph representation of a junction associated with the road segment including a plurality of nodes and one or more semantic links; provide the graph representation to a trained model configured to infer a relationship between the road element and the lane of travel; based on the output of the trained model, store in the map road element relationship; and distribute the map for use in navigating along the road segment.

Abstract: A Printed Circuit Board (PCB) may include one or more single-ended PCB traces configured to route single-ended Radio-Frequency (RF) signals between an integrated circuit and one or more waveguides, wherein first ends of the one or more single-ended PCB traces are to be coupled to the integrated circuit; and one or more PCB-to-waveguide transitions configured to couple second ends of the one or more single-ended PCB traces to the one or more waveguides. For example, a PCB-to-waveguide transition may include a PCB probe connected to a second end of a single-ended PCB trace of the one or more single-ended PCB traces, the PCB probe configured to couple RF energy of the single-ended RF signals between the single-ended PCB trace and a waveguide of the one or more waveguides; and a via configured to electrically connect the PCB probe to a ground layer of the PCB.

Abstract: Systems and methods may generate a map for use in navigating a host vehicle relative to a road segment by receiving drive information from a vehicle that previously traversed the road segment, providing a representation of at least one road topography indicator to a trained model, wherein the trained model is configured to provide a driving protocol indicator as an output; generating, based on the driving protocol indicator, a representation of at least one driving convention associated with the driving protocol indicator and storing the representation of the at least one driving convention in the map; and distributing the map to at least one host vehicle navigation system for use in navigating the host vehicle along the road segment relative to the stored representation of the at least one driving convention.

Abstract: A system for navigating a host vehicle relative to a road segment may store a speed limit indicator in a map among navigation information associated with the road segment. The system may determine a first navigational action for the host vehicle based on the received speed limit indicator; cause at least one system associated with the host vehicle to implement the first navigational action; receive an image acquired by at least one camera onboard the host vehicle; determine a speed limit affecting condition represented in the received image; determine a condition-based speed limit based on the speed limit affecting condition; determine a second navigational action for the host vehicle based on the condition-based speed limit; and cause the at least one system associated with the host vehicle to implement the second navigational action.

Abstract: System and methods are disclosed for navigating a host vehicle. In one implementation, at least one processing device may be programmed to receive a plurality of images representative of an environment of the host vehicle, identify, in at least one of the plurality of images a representation of, a target vehicle, determine a separation distance between the host vehicle and the target vehicle, if the separation distance is less than a comfort distance threshold, cause a reduction in a throttle level associated with a throttle system of the host vehicle without activating a braking system associated with the host vehicle, and if the separation distance is determined to be greater than but trending toward a safe distance threshold, which is less than the comfort distance threshold, cause activation of the braking system associated with the host vehicle.

Abstract: Systems and methods are provided for navigating a host vehicle.

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: Techniques are disclosed for reducing false positives for generating warnings to avoid potential collisions between a vehicle and vulnerable road users (VRUs). This is accomplished via an onboard vehicle safety system that uses crowdsourced map data to determine whether a vehicle is capable of performing a maneuver that results in a lateral shift of the vehicle (which may include a lane-shifting or turning maneuver) within a predetermined threshold time period. The ability for the vehicle to make the turning maneuver, among other driving scenarios, may be used to by the safety system to intelligently determine whether a warning or other action is needed to avoid a potential collision with a VRU. In this way, the occurrence and number of false warnings/interventions are minimized or at least reduced, leading to more attentive drivers and thereby improving VRU safety.

Abstract: For example, a polarized antenna may include a dielectric layer including an antenna via; a first metal layer on a first side of the dielectric layer, the first metal layer including an antenna feeding trace connected to a first end of the antenna via; and a second metal layer on a second side of the dielectric layer. For example, the second metal layer may include a plurality of antenna elements including a first antenna element, a second antenna element, and a third antenna element. For example, the third antenna element may be connected to a second end of the antenna via. For example, the second metal layer may include a plurality of antenna traces serially connecting the plurality of antenna elements.

Abstract: Techniques are disclosed to enable the generation of ground truth datasets that identify a continuous time movement trajectory of dynamic objects such as non-stationary vehicles. The techniques as described herein may utilize iterative closest point (ICP) processes to compute a rigid-body transform that describes a 3D correspondence between different pairs of temporal point cloud data sample sets at various discrete time periods that are identified with an object along a movement trajectory. From these rigid-body transforms at each of the discrete time periods, a pose graph optimization may be performed to compute the continuous time movement trajectory. The ground truth datasets may be used to enable training of machine learning models, which may be used by a vehicle computing system when navigating a driving environment.

Abstract: The disclosed technique is an any-in, first-out (“AIFO”) memory device that improves upon conventional first-in, first-out memory devices. The technique mimics a first-in, first-out queue to provide sequential storage and retrieval in scenarios where transactional ordering cannot be guaranteed. By associating an identifier and a write-pointer in a look-up table with read requests prior to transmission, responses may be received out of order and/or interleaved without delaying processing until the next response in the sequence is received. An internal validity flag may be included in the AIFO memory array to represent the validity of each line in the memory array. Once a read pointer reaches a row that is marked as invalid, the read command pauses and discontinues further reading until a write to the row that marks the row as valid. To further optimize writing, a polarity of the validity may be toggled each read cycle.