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: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system includes a processing device programmed to receive a plurality of images representative of an environment of the host vehicle. The environment includes a road on which the host vehicle is traveling. The at least one processing device is further programmed to analyze the images to identify a target vehicle traveling in a lane of the road different from a lane in which the host vehicle is traveling; analyze the images to identify a lane mark associated with the lane in which the target vehicle is traveling; detect lane mark characteristics of the identified lane mark; use the detected lane mark characteristics to determine a type of the identified lane mark; determine a characteristic of the target vehicle; and determine a navigational action for the host vehicle based on the determined lane mark type and the determined characteristic of the target vehicle.

Abstract: A system that may include multiple driving related systems that are configured to perform driving related operations; a selection module; multiple fault collection and management units that are configured to monitor statuses of the multiple driving related systems and to report, to the selection module, at least one out of (a) an occurrence of at least one critical fault, (b) an absence of at least one critical fault, (c) an occurrence of at least one non-critical fault, and (d) an absence of at least one non-critical fault; and wherein the selection module is configured to respond to the report by performing at least one out of: (i) reset at least one entity out of the multiple fault collection and management units and the multiple driving related systems; and (ii) select data outputted from a driving related systems.

Abstract: A driving related system that may include an integrated circuit (IC) that may include IC conductors and test unit; a PCB that may include PCB conductors; intermediate conductors for coupling the IC conductors to the PCB conductors; wherein the test unit is configured to: electrically test a continuity of a first conductive path that comprises a first group of intermediate conductors, a first group of IC conductors and a first group of PCB conductors; and generate a continuity fault indication when detecting a discontinuity of the first conductive path; and wherein the driving related system is configured to perform a safety measure, in response to a generation of one or more continuity fault indications.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a navigational system for a host vehicle may include at least one processor programmed to: receive a stream of images captured by a camera onboard the host vehicle, wherein the captured images are representative of an environment surrounding the host vehicle; and receive an output of a LIDAR onboard the host vehicle, wherein the output of the LIDAR is representative of a plurality of laser reflections from at least a portion of the environment surrounding the host vehicle.

Abstract: A navigation system may include a processor programmed to analyze a first image to identify a non-semantic road feature; identify a first image location, in the first image, of one point associated with the non-semantic road feature; analyze a second image to identify a representation of the non-semantic road feature in the second image; identify a second image location, in the second image, of the one point associated with the non-semantic road feature; determine, based on a difference between the first and second image locations and based on motion information for a vehicle between a capture of the first image and a capture of the second image, three-dimensional coordinates for the one point associated with the non-semantic road feature; and send the three-dimensional coordinates for the one point associated with the non-semantic road feature to a server for use in updating a road navigation model.

Abstract: Apparatuses, storage media and methods associated with computer assisted driving (CAD), are disclosed herein. In some embodiments, an apparatus includes an autopilot engine to automatically pilot the vehicle out of a potential emergency situation, including to automatically pilot the vehicle for a period of time in view of a plurality of operational guardrails determined in real time for each of a plurality of timing windows; and a mitigation unit to conditionally activate the autopilot engine, including to activate the autopilot engine in response to analysis results indicative of the vehicle being potentially operated into the emergency situation manually. Other embodiments are also described and claimed.

Abstract: A navigation system may include a processor programmed to receive, from a camera of the host vehicle, one or more images captured from an environment of the host vehicle, and analyze the one or more images to detect an indicator of an intersection. The processor may also be programmed to 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, and analyze the one or more images to determine an indicator of whether one or more other vehicles are in front of the host vehicle. The processor may further be programmed to 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: 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 profile, a maximum acceleration capability, and a current speed of the host vehicle; determine a stopping distance for the target vehicle based on a braking profile 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: Autonomous driving system methods and devices which trigger vehicular actions based on the monitoring of one or more occupants of a vehicle are presented. The methods, and corresponding devices, may include identifying a plurality of features in a plurality of subsets of image data detailing the one or more occupants; tracking changes over time of the plurality of features over the plurality of subsets of image data; determining a state, from a plurality of states, of the one or more occupants based on the tracked changes; and triggering the vehicular action based on the determined state.

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 are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive an image associated with the environment of the host vehicle. The processor may analyze the image to identify a side of a parked vehicle; a first structural feature of the parked vehicle in a forward region of the side of the parked vehicle or a second structural feature of the parked vehicle in a rear region of the side of the parked vehicle; and a door feature of the parked vehicle in a vicinity of the first or the second structural features. The processor may then determine, based on a subsequent image, a change of an image characteristic of the door feature of the parked vehicle and alter a navigational path of the host vehicle based on the change of the image characteristic.

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 are provided for navigating a host vehicle. At least one 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 in the environment of the host vehicle; determine a next-state lateral distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a lateral braking distance for the host vehicle and the target vehicle based on a maximum yaw rate capability, a maximum change in turn radius capability, and a current lateral speed of the host vehicle and the target vehicle; and implement the planned navigational action if the determined next-state distance is greater than a sum of the lateral braking distances for the host vehicle and the target vehicle.

Abstract: Autonomous vehicles are an exciting prospect to the future of driving. However, concerns about the decision-making made by the AI controlling a vehicle has been of concern, particularly in light of high-profile accidents. We can alleviate some concern, introduce better decisions, and also train an AI to make better decisions by introducing a remote viewer's, e.g., a human's, reaction to a possibly complex environment surrounding a vehicle that includes a potential threat to the vehicle. One or more remote viewer may provide a recommended response to the threat that may be incorporated in whole or in part in how the vehicle reacts. Various ways to engage and utilize remote viewers are proposed to improve the likelihood of receiving useful recommendations, including modifying how the environment is presented to a remote viewer to best suit the remote viewer, e.g., perhaps present the threat in a game.

Abstract: The present disclosure relates to navigational systems for vehicles. In one implementation, such a navigational system may a first output from a first sensor and a second output from a second sensor; identify a target object in the first output; and determine, based on the first output, a detected driving condition associated with the target object and whether the condition triggers a navigational constraint. If the navigational constraint is triggered, the system may cause a first navigational adjustment. If the navigational constraint is not triggered, the system may determine whether a representation of the target object is included in the second output. If the representation of the target object is included in the second output, the system may cause a second navigational adjustment. If the representation of the target object is not included in the second output, the system may forego any navigational adjustments.

Abstract: Spatial data may be divided along an axis of the second dimension into a first data segment and a second data segment, such that the first data segment is limited to data points of the spatial data with second dimension coordinates within a first range and the second data segment is limited to data points of the spatial data with second dimension coordinates within a second range. A first processing element may execute an object detection process on the first data segment to generate a first list of objects within the first data segment. A second processing element may execute the object detection process on the second data segment to generate a second list of objects within the second data segment. A first set of objects detected in the first data segment may be combined with a second set of objects detected in the second data segment.

Abstract: A method for collecting data from a group of entitled members. The method may include receiving, by a collection unit, a message and a message signature; validating, by the collection unit, whether the message was received from any of the entitled members of the group, without identifying the entitled member that sent the message; wherein the validating comprises applying a second plurality of mathematical operations on a first group of secrets, a second group of secrets, and a first part of the message signature; and rejecting, by the collection unit, the message when validating that the message was not received from any entitled member of the group.

Abstract: A system, computer readable medium and a method that may include performing multiple iterations of: determining, by each active initiator of the multiple initiators, a number of pending access requests generated by the active initiator, wherein each access request is a request to access a shared resource out of the shared resources; determining, by each active initiator, a priority level to be assigned to all pending access requests generated by the active initiator, wherein the determining is based on the number of pending access requests generated by the active initiator, a number of active initiators out of the multiple initiators, and a number of access requests serviceable by the shared resource; for each active initiator, informing an arbitration hardware of a network on chip about the priority level to be assigned to all pending access requests generated by the active initiator; and managing access to the shared resources, by the arbitration hardware, based on the priority level to be assigned to all p

Abstract: System and techniques for vehicle environment modeling with a camera are described herein. A device for modeling an environment comprises: a hardware sensor interface to obtain a sequence of unrectified images representative of a road environment, the sequence of unrectified images including a first unrectified image, a previous unrectified image, and a previous-previous unrectified image; and processing circuitry to: provide the first unrectified image, the previous unrectified image, and the previous-previous unrectified image to an artificial neural network (ANN) to produce a three-dimensional structure of a scene; determine a selected homography; and apply the selected homography to the three-dimensional structure of the scene to create a model of the road environment.