Abstract: Systems and methods for navigating a host vehicle are disclosed. In one implementation at least one processor is programmed to receive two or more images captured by a camera of the host vehicle from an environment of the host vehicle; analyze the two or more images to identify a representation of at least a portion of a first object and a representation of at least a portion of a second object; determine a first region of the two or more images associated with the first object and a type of the first object; and determine a second region of the two or more images associated with the second object and type of the second object, wherein the type of the first object is different from the type of the second object.

Abstract: A system for mapping a lane mark for use in autonomous vehicle navigation is provided. The system includes at least one processor programmed to receive two or more location identifiers associated with a detected lane mark, associate the detected lane mark with a corresponding road segment, update an autonomous vehicle road navigation model relative to the corresponding road segment based on the two or more location identifiers associated with the detected lane mark, and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Abstract: Systems and methods are provided for navigating based on behaviors of following vehicles. In one implementation, a navigation system for a host vehicle may include at least one processing device. The at least one processing device may be 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 a first target vehicle and a second target vehicle in the environment of the host vehicle; analyze the plurality of images to determine a distance between the first target vehicle and the second target vehicle; and determine, from the plurality of images, a time to reach a boundary associated with one of the first target vehicle and the second target vehicle, wherein the determined time exceeds a first threshold and does not exceed a second threshold.

Abstract: A processing unit, where the processing unit one of a group of processing units of a system, includes a processor; and memory including instructions, which when executed by the processor while avoiding interrupting a controller that does not belong to the group of processing units, cause the processor to: perform at least one iteration of the steps of: (a) entering a trusted mode, (b) selecting a selected job to be executed by the processing unit, (c) retrieving access control metadata related to the selected job, (d) entering, by the processing unit, an untrusted mode, (e) executing the selected job by the processing unit while adhering to the access control metadata related to the job, and (f) resetting the processing unit.

Abstract: Techniques are disclosed for an unsafe hot spot detection and reporting system to identify unsafe “hotspot” zones. The system functions to identify hotspot zones that are associated with an increased number of detected warnings regarding unsafe conditions, vehicle collisions, near misses, or other hazardous events. The hotspots are determined based upon historical data that may include safety-based warnings issued from vehicle with respect to in-vehicle monitoring data or other data sources. The system leverages the hotspot location information to identify a safety data model (SDM) rule and automatically adjust one or more safety data model (SDM) parameters of the SDM rule such as follow distance, speed settings, etc., and/or to route the vehicle to an alternate course to avoid an identified unsafe hotspot zone.

Abstract: A vehicle navigation system for detecting and responding to a cut-in by a target vehicle is disclosed. The vehicle navigation system includes at least one processor configured to receive image data captured by an image capture device of the host vehicle; identify, based on analysis of the image data, a target vehicle traveling in a lane adjacent to a lane in which the host vehicle is traveling; determine, based on analysis of the image data, that a predetermined cut in sensitivity change factor is present; and based on the determination that the predetermined cut in sensitivity change factor is present, cause a navigational response in the host vehicle.

Abstract: Disclosed embodiments provide systems and methods that can be used as part of or in combination with autonomous navigation, autonomous driving, or driver assist technology features. As opposed to fully autonomous driving, driver assist technology may refer to any suitable technology to assist drivers in the navigation or control of their vehicles. In various embodiments, the system may include one or more cameras mountable in a vehicle and an associated processor that monitors the environment of the vehicle. In further embodiments, additional types of sensors can be mounted in the vehicle and can be used in the autonomous navigation or driver assist systems. These systems and methods may include the use of a shared cache that is shared by a group of processing units to improve analysis of images captured by the one or more cameras.

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: Techniques are disclosed for updating a trusted software and another software, which may include receiving a software update package that comprises a trusted updated software component, a trusted updated software booting metadata, another updated software component, and another updated software booting metadata. The trusted updated software component may belong to an updated version of the trusted software, and the trusted software may have a certain trust level. The other updated software component may belong to an updated version of the other software, and the other software may have a trust level that is lower than the certain trust level. At least a part of the trusted updated software booting metadata may comprise retrieval information for retrieving, during a booting process, at least a portion of the other software booting metadata.

Abstract: Systems and methods are provided for processing reports received from vehicles. A processing device perform operations comprising receiving a first report generated by a first vehicle, the first report generated by the first vehicle for a first hazard detected by the first vehicle; receiving a second report generated by a second vehicle, the second report generated by the second vehicle for a second hazard detected by the second vehicle; analyzing the first report and the second report to make a determination that the first report and the second report identify a related hazard; aggregating the first report and the second report into a consolidated report based on the determination that the first report and the second report identify a related hazard; and generating a map, the map indicating a location of the related hazard based on the consolidated report.

Abstract: Systems and methods for navigating a host vehicle are disclosed. In one implementation at least one processor is programmed to receive a first signature encoding generated by a first trained model implemented by a first processor associated with a first camera; receive a second signature encoding generated by a second trained model implemented by a second processor associated with a second camera; input the first signature encoding and the second signature encoding into a third trained model, wherein the third trained model is configured to determine a location of an object represented in the first image and the second image; and receive an indicator of the location of the object determined by the third trained model.

Abstract: For example, a pixel processor may be configured to receive signed digital pixel data corresponding to a plurality of pixels of a pixel array, the signed digital pixel data including a plurality of pixel-read values over a signed range, the plurality of pixel-read values including a plurality of negative pixel-read values over a negative sub-range, and a plurality of positive pixel-read values over a positive sub-range; and to generate unsigned digital pixel data over an unsigned range based on the signed digital pixel data, the unsigned digital pixel data including a first plurality of unsigned digital pixel values over a first sub-range of the unsigned range, and a second plurality of unsigned digital pixel values over a second sub-range of the unsigned range. For example, the first plurality of unsigned digital pixel values may be based on a black level scaling factor applied to the plurality of negative pixel-read values.

Abstract: Techniques are disclosed for using augmented reality (AR) displays to convey graphical representations of different types of information to a user. The information may be obtained from various sources such as objects and/or features that are dynamically detected by a vehicle or user-generated content. The graphical representations may also be based upon information that may be obtained via the use of crowdsourced AV map data. The graphical representations may be presented in as an AR view in a medium (such as a vehicle windshield) that matches a field of view of a user, thus accurately blending holographic information with the physical objects in the scene.

Abstract: A non-transitory computer-readable medium is provided. The computer-readable medium includes a sparse map for autonomous vehicle navigation along a road segment. The sparse map includes a polynomial representation of a target trajectory for the autonomous vehicle along the road segment, and a plurality of predetermined landmarks associated with the road segment. The sparse map has a data density of no more than 1 megabyte per kilometer.

Abstract: Systems and methods are provided for navigating a host vehicle. A processing device may be programmed to receive an image representative of an environment of the host vehicle; determine a planned navigational action for the host vehicle; analyze the image to identify a target vehicle travelling toward the host vehicle; determine a next-state distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a stopping distance for the host vehicle based on a braking rate, a maximum acceleration capability, and a current speed of the host vehicle; determine a stopping distance for the target vehicle based on a braking rate, a maximum acceleration capability, and a current speed of the target vehicle; and implement the planned navigational action if the determined next-state distance is greater than a sum of the stopping distances for the host vehicle and the target vehicle.

Abstract: Systems and methods are provided for navigating a host vehicle. At least one processing device may be programmed to receive an image of an environment of the host vehicle; detect, based on analysis of the image, a pedestrian crosswalk in the image; detect a presence of a traffic light and determine whether the traffic light is relevant to the host vehicle and the pedestrian crosswalk; determine a state of the traffic light; determine, when a pedestrian appears in the image, a proximity of the pedestrian relative to the pedestrian crosswalk; determine a planned navigational action for navigating the host vehicle relative to the pedestrian crosswalk based on a driving policy, the state of the traffic light and the proximity of the pedestrian relative to the pedestrian crosswalk; and cause one or more actuator systems of the host vehicle to implement the planned navigational action.

Abstract: Systems and methods described herein can be used to improve camera modules (e.g., camera components), particularly when the camera lens depth of focus is very small. Improvement of a camera with a small depth of focus is particularly important in various applications, such as in cameras used in autonomous navigation (e.g., advanced driver assistance systems (ADAS) and autonomous vehicle (AV) systems).