Abstract: Systems and methods of processing crowdsourced navigation information for use in autonomous vehicle navigation are disclosed. A method may include processing, by a mapping server, crowdsourced navigation information from a plurality of vehicles obtained by sensors coupled to the plurality of vehicles, wherein the navigation information describes road lanes of a road segment; collecting data about landmarks identified proximate to the road segment, the landmarking including a traffic sign; generating, by the mapping server, an autonomous vehicle map for the road segment, wherein the autonomous vehicle map includes a spline corresponding to a lane in the road segment and the landmarks identified proximate to the road segment; and distributing, by the mapping server, the autonomous vehicle map to an autonomous vehicle for use in autonomous navigation over the road segment.

Abstract: Systems and methods for navigating a host vehicle. The system may perform operations including receiving, from an image capture device, at least one image representative of an environment of the host vehicle; analyzing the at least one image to identify an object in the environment of the host vehicle; determining a location of the host vehicle; receiving map information associated with the determined location of the host vehicle, wherein the map information includes elevation information associated with the environment of the host vehicle; determining a distance from the host vehicle to the object based on at least the elevation information; and determining a navigational action for the host vehicle based on the determined distance.

Abstract: A navigation system for a host vehicle may include a processor programmed to: receive, from an entity remotely located relative to the host vehicle, a sparse map associated with at least one road segment to be traversed by the host vehicle; receive point cloud information from a LIDAR system onboard the host vehicle, the point cloud information being representative of distances to various objects in an environment of the host vehicle; compare the received point cloud information with at least one of the plurality of mapped navigational landmarks in the sparse map to provide a LIDAR-based localization of the host vehicle relative to at least one target trajectory; determine an navigational action for the host vehicle based on the LIDAR-based localization of the host vehicle relative to the at least one target trajectory; and cause the at least one navigational action to be taken by the host vehicle.

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.

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 images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

Abstract: A navigational system for a host vehicle may comprise at least one processing device. The processing device may be programmed to receive a first output and a second output associated with the host vehicle; identify a representation of a target object in the first output; and determine whether a characteristic of the target object triggers a navigational constraint. If the navigational constraint is not triggered, the processing device may verify the identification of the representation of the target object based on a combination of the first output and the second output. If the navigational constraint is triggered, the processing device may verify the identification of the representation of the target object based on the first output; and in response to the verification, cause at least one navigational change to the host vehicle.

Abstract: Systems and methods are provided for processing reports received from vehicles. A processing device perform operations comprising receiving a first report from a first vehicle, the first report generated by the first vehicle for a first hazard detected by the first vehicle; receiving a second report from 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 processing the consolidated report to identify a contributing factor to the related hazard.

Abstract: A system for a vehicle is provided. The system may include a memory and at least one processor configured to: access a plurality of images of a forward-facing view from the vehicle, the plurality of images corresponding to image data obtained by a camera; determine from the images a first lane marking on a first side of a lane, the lane through which the vehicle can navigate, and a second lane marking on a second side of the lane opposite of the first side; navigate the vehicle autonomously relatively centered between the first and second lane markings; determine from the plurality of images that an object is on the first side or the second side of the lane, and the object beyond the first or second lane marking; and navigate the vehicle autonomously to travel over a driving path that is offset from a center of the lane.

Abstract: A system for determining safety of a road segment may include at least one processor programmed to receive, from a first vehicle, first navigation information associated with the road segment. The first navigation information may include information collected by a first sensor of the first vehicle from an environment of the first vehicle. The at least one processor may also be programmed to receive, from a second vehicle, second navigation information associated with the road segment. The second navigation information may include information collected by a second sensor of the second vehicle from an environment of the second vehicle. The at least one processor may further be programmed to determine, based on the first navigation information and the second navigation information, a score representative of the safety of the road segment, and transmit, to a third vehicle, the score representative of the safety of the road segment.

Abstract: A system for managing storage space for a computer may include at least one processor programmed to determine a maximum data space for a computing task. The at least one processor may also be programmed to create a file having a maximum size equal to or greater than the maximum data space. The at least one processor may further be programmed to create a virtual device linked to the file and mount a filesystem inside the virtual device. The at least one processor may also be programmed to mount the virtual device. The at least one processor may further be programmed to determine that the computing task is completed. The at least one processor may further be programmed to unmount the virtual device.

Abstract: An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a system for a host vehicle includes at least one processor programmed to determine, based on an output of at least one sensor of the host vehicle, one or more target dynamics of a target vehicle; determine, based on one or more host dynamics of the host vehicle and the target dynamics, a time to collision; determine, based on the time to collision and the host dynamics, a host deceleration for the host vehicle to avoid the collision; determine, based on the time to collision and the target dynamics, a target deceleration for the target vehicle to avoid the collision; determine, based on the host deceleration and the target deceleration, a host deceleration threshold; and determine, based on a speed of the host vehicle and the host deceleration threshold, to brake the host vehicle.

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 road segment. The processor may divide the first navigational information into at least a first portion and a second portion; divide the second navigational information into at least a first portion and a second portion; align the first portion of the first navigational information with the first portion of the second navigational information; align the second portion of the first navigational information with the second portion of the second navigational information; generate a road model based on the aligned portions; and send the road model to vehicles for use in navigating along the road segment.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a driver-assist object detection system is provided for a vehicle. One or more processing devices associated with the system receive at least two images from a plurality of captured images via a data interface. The device(s) analyze the first image and at least a second image to determine a reference plane corresponding to the roadway the vehicle is traveling on. The processing device(s) locate a target object in the first two images, and determine a difference in a size of at least one dimension of the target object between the two images. The system may use the difference in size to determine a height of the object. Further, the system may cause a change in at least a directional course of the vehicle if the determined height exceeds a predetermined threshold.

Abstract: An imaging system is provided for a vehicle. In one implementation, the imaging system includes an imaging module, a first camera coupled to the imaging module, a second camera coupled to the imaging module, and a mounting assembly configured to attach the imaging module to the vehicle such that the first and second camera face outward with respect to the vehicle. The first camera has a first field of view and a first optical axis, and the second camera has a second field of view and a second optical axis. The first optical axis crosses the second optical axis in at least one crossing point of a crossing plane. The first camera is focused a first horizontal distance beyond the crossing point of the crossing plane and the second camera is focused a second horizontal distance beyond the crossing point of the crossing plane.

Abstract: Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise an interface to obtain sensing data of an environment of the host vehicle. The processing device may be configured to determine a planned navigational action; identify, a target vehicle in the environment of the host vehicle; predict a distance between the host vehicle and the target vehicle if the planned navigational action was taken; determine a current host vehicle stopping distance based on a braking capability, acceleration capability, and speed of the host vehicle; determine a current target vehicle braking distance based on a speed and braking capability of the target vehicle; and implement the planned navigational action when the predicted distance of the planned navigational action is greater than a minimum safe longitudinal distance calculated based on the current host vehicle stopping distance and the current target vehicle braking distance.

Abstract: A method including operations to obtain a planned driving action for accomplishing a navigational goal of a host vehicle on a roadway, identify a planned trajectory for the host vehicle, corresponding to the planned driving action, identify, from sensor data representative of an environment of the host vehicle, an occluded location of a potential object that is occluded from view of the host vehicle, identify a possible trajectory of the potential object, based on possible movement of the potential object from the location into the roadway, identify an intersection of the planned trajectory for the host vehicle with the possible trajectory for the potential object, determine a safety action of the host vehicle to respond to the possible movement of the potential object, and apply the safety action to change the planned driving action of the host vehicle.

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: An accident liability tracking system includes a processing device programmed to receive, from an image capture device, an image representative of an environment of the host vehicle, to analyze the image to identify a target vehicle in the environment of the host vehicle, and determine one or more characteristics of a navigational state of the target vehicle. The device is further programmed to compare the characteristics of the navigational state of the target vehicle to at least one accident liability rule, store one or more values indicative of potential accident liability on the part of the identified target vehicle based on the comparison of the characteristics of the navigational state of the identified target vehicle to the at least one accident liability rule, and output the one or more values, after an accident between the host vehicle and a target vehicle, for determining liability for the accident.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a driver-assist object detection system is provided for a vehicle. One or more processing devices associated with the system receive at least two images from a plurality of captured images via a data interface. The device(s) analyze the first image and at least a second image to determine a reference plane corresponding to the roadway the vehicle is traveling on. The processing device(s) locate a target object in the first two images, and determine a difference in a size of at least one dimension of the target object between the two images. The system may use the difference in size to determine a height of the object. Further, the system may cause a change in at least a directional course of the vehicle if the determined height exceeds a predetermined threshold.