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:
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 plurality of predetermined landmarks are spaced apart by at least 50 meters, and the sparse map has a data density of no more than 1 megabyte per kilometer.
Abstract:
A system for autonomously navigating a vehicle is disclosed. The system may include at least one processor and the at least one processor may be programmed to receive from a rearward facing camera, at least one image representing an area at a rear of the vehicle and analyze the at least one rearward facing image to locate in the image a representation of at least one landmark. The at least one processor may be further programmed to determine at least one indicator of position of the landmark relative to the vehicle and determine a forward trajectory for the vehicle based, at least in part, upon the indicator of position of the landmark relative to the vehicle. Additionally, the at least one processor may be programmed to cause the vehicle to navigate along the determined forward trajectory.
Abstract:
A computerized system mountable on a vehicle operable to detect an object by processing first image frames from a first camera and second image frames from a second camera. A first range is determined to said detected object using the first image frames. An image location is projected of the detected object in the first image frames onto an image location in the second image frames. A second range is determined to the detected object based on both the first and second image frames. The detected object is tracked in both the first and second image frames When the detected object leaves a field of view of the first camera, a third range is determined responsive to the second range and the second image frames.
Abstract:
A system for a host vehicle includes a processor programmed to receive, from an image capture device, an image representative of an environment of the host vehicle, detect at least one obstacle in the environment of the host vehicle based on an analysis of the at least one image, determine a velocity of the host vehicle and a predicted path for the host vehicle, monitor a driver input to at least one of a throttle control, a brake control, or a steering control associated with the host vehicle, and determine whether the driver input would result in the host vehicle navigating within a proximity buffer relative to the at least one obstacle, wherein the proximity buffer is determined based on the determined velocity, a maximum acceleration capacity of the host vehicle, and a maximum braking capacity of the host vehicle, and a reaction time associated with the host vehicle.
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:
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:
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 plurality of predetermined landmarks are spaced apart by at least 50 meters, and the sparse map has a data density of no more than 1 megabyte per kilometer.
Abstract:
A system for navigating an autonomous vehicle along a road segment is disclosed. The system may have at least one processor. The processor may be programmed to receive from an image capture device, images representative of an environment of the autonomous vehicle. The processor may also be programmed to determine a travelled trajectory along the road segment based on analysis of the images. Further, the processor may be programmed to determine a current location of the autonomous vehicle along a predetermined road model trajectory based on analysis of one or more of the plurality of images. The processor may also be programmed to determine a heading direction based on the determined traveled trajectory. In addition, the processor may be programmed to determine a steering direction, relative to the heading direction, by comparing the traveled trajectory to the predetermined road model trajectory at the current location of the autonomous vehicle.
Abstract:
A method of processing vehicle navigation information for use in autonomous vehicle navigation is provided. The method includes receiving, by a server, navigation information from a plurality of vehicles. The navigation information from the plurality of vehicles is associated with a common road segment. The method also includes storing, by the server, the navigation information associated with the common road segment. The method also includes generating, by the server, at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles. The method further includes distributing, by the server, 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 segment.