Abstract: An autonomous system includes a processing device programmed to receive, from an image capture device, an image of an environment of the host vehicle; detect an obstacle in the environment, based on an analysis of the image; monitor a driver input to at least one of a throttle control, a brake control, or a steering control associated with the host vehicle; determine whether the driver input results in the host vehicle navigating within a proximity buffer relative to the obstacle; allow the driver input to cause a corresponding change in one or more host vehicle motion control systems, if the processing device determines that the driver input would not result in the host vehicle navigating within the proximity buffer relative to the obstacle; and prevent the driver input to cause the change if the driver input results in the host vehicle navigating within the proximity buffer relative to the obstacle.

Abstract: In some embodiments, a first homography, created from two images of a roadway, is decomposed to determine an ego-motion, and the ego-motion is used to adjust a previous estimate of a road plane. The adjusted previous estimate of the road plane is combined with the current estimate of the plane to create a second homography, and the second homography is used to determine residual motion and vertical deviation in the surface of the roadway. In some embodiments, multiple road profiles each corresponding to a common portion of a roadway are adjusted in slope and offset by optimizing a function having a data term, a smoothness term and a regularization term; and the adjusted road profiles are combined into a multi-frame road profile. In some embodiments, road profile information for a predetermined number of data points is transmitted in periodic data bursts, with more than one data point per data burst.

Abstract: Systems and methods use cameras to provide autonomous and/or driver-assist navigation features. In some implementations, techniques for predicting the location of first roadway lane constraints are provided. The system may receive multiple images of a roadway in a vicinity of a vehicle, recognize a first roadway lane constraint, and, when lane prediction conditions are determined to be satisfied, predict a location of a second roadway lane constraint. In some implementations, techniques for detecting and responding to construction zones are provided. The system may receive multiple images of a roadway in a vicinity of a vehicle, recognize indicators of a construction zone in the images, determine that the vehicle is proximate to a construction zone, and output a signal indicating that the vehicle is proximate to a construction zone.

Abstract: A system for autonomously navigating a vehicle along a road segment may include at least one processor. The at least one processor may be programmed to receive from at least one sensor information relating to one or more aspects of the road segment. The processor may also be programmed to determine a local feature of the road segment based on the received information. Further the processor may be programmed to compare the local feature to a predetermined signature feature for the road segment. The processor may be programmed to determine a current location of the vehicle along a predetermined road model trajectory associated with the road segment based on the comparison of the received information and the predetermined signature feature. The processor may also be programmed to determine an autonomous steering action for the vehicle based on a direction of the predetermined road model trajectory at the determined location.

Abstract: A system mountable in a motor vehicle. The system includes a camera and a processor configured to receive image data from the camera. The camera includes a rolling shutter configured to capture the image data during a frame period and to scan and to read the image data into multiple image frames. A near infra-red illuminator may be configured to provide a near infra-red illumination cone in the field of view of the camera. The near infra-red illumination oscillates with an illumination period. A synchronization mechanism may be configured to synchronize the illumination period to the frame period of the rolling shutter. The frame period may be selected so that the synchronization mechanism provides a spatial profile of the near infra-red illumination cone which may be substantially aligned vertically to a specific region, e.g. near the center of the image frame.

Abstract: The present disclosure relates to systems and methods for host vehicle navigation. In one implementation, a navigation system for a host vehicle may include at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the images to identify a target vehicle in the environment of the host vehicle; cause a navigational change of the host vehicle to signal to the target vehicle an intent of the host vehicle to make a subsequent navigational maneuver; analyze the images to detect a change in a navigational state of the target vehicle; determine a navigational action for the host vehicle; and cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action for the host vehicle.

Abstract: A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

Abstract: System and techniques for vehicle environment modeling with a camera are described herein. A time-ordered sequence of images representative of a road surface may be obtained. An image from this sequence is a current image. A data set may then be provided to an artificial neural network (ANN) to produce a three-dimensional structure of a scene. Here, the data set includes a portion of the sequence of images that includes the current image, motion of the sensor from which the images were obtained, and an epipole. The road surface is then modeled using the three-dimensional structure of the scene.

Abstract: Systems and methods are provided for determining a lane assignment for an autonomous vehicle along a road segment. In one implementation, at least one image representative of an environment of the vehicle is received from a camera. The at least one image may be analyzed to identify at least one recognized landmark, and an indicator of a lateral offset distance between the vehicle and the at least one recognized landmark may be determined. Moreover, a lane assignment of the vehicle along the road segment may be determined based on the indicator of the lateral offset distance between the vehicle and the at least one recognized landmark.

Abstract: Computing a time-to-contact (TTC) of a vehicle with an object. The object includes a light source. The system mountable in the vehicle includes a camera and a processor configured to capture images of the object. The processor is operable to track a spot between the images to produce a tracked spot. The spot includes an image of the light source. The processor is operable to compute time-to-contact (TTC) responsive to changes in brightness of the tracked spot.

Abstract: A navigation system includes a processor programmed to receive, from a sensor, an output related to a motion of the host vehicle. The output is generated at a first time that is later than a data acquisition time, when a measurement or data acquisition on which the output is based is acquired, and earlier than a second time at which the sensor output is received processor; generate, for a motion prediction time, a prediction of at least one aspect of host vehicle motion based, on the output and how the aspect of host vehicle motion changes over a time interval between the data acquisition time and the motion prediction time; determine a navigational action for the host vehicle; generate a navigational command for implementing at least a portion of the navigational action; and provide the navigational command to at least one actuation system of the host vehicle.

Abstract: A system for navigating a host vehicle may: receive, from an image capture device, an image representative of an environment of the host vehicle; determine a navigational action for accomplishing a navigational goal of the host vehicle; analyze the image to identify a target vehicle in the environment of the host vehicle; determine a next-state distance between the host vehicle and the target vehicle that would result if the navigational action was taken; determine a maximum braking capability of the host vehicle, a maximum acceleration capability of the host vehicle, and a speed of the host vehicle; determine a stopping distance for the host vehicle; determine a speed of the target vehicle and assume a maximum braking capability of the target vehicle; and implement the navigational action if the stopping distance for the host vehicle is less than the next-state distance summed together with a target vehicle travel distance.

Abstract: Systems and methods are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: Systems and methods are provided for augmenting upright object detection. In one implementation, a system for augmenting detection of objects in an environment of a vehicle may include at least one processing device. The at least one processing device may be programmed to: receive, from an image capture device, a first image frame, the first image frame including an attention area associated with a suspected upright object indication; warp, using a level road plane model, an area in a second earlier image frame that corresponds to the attention area; track a plurality of image patches across the warped area and the attention area; compute a road plane model fit to the tracked image patches; and determine whether to suppress the upright object indication based on the tracked image patches being more consistent with a road plane model than with an upright object model.

Abstract: Systems and methods are provided for distributing a crowdsourced sparse map for autonomous vehicle navigation. In one implementation, a method of generating a road navigation model for use in autonomous vehicle navigation may include receiving navigation information associated with a common road segment from a plurality of vehicles; storing the navigation information associated with the common road segment; generating at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information; and distributing the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating along the common road segment. The autonomous vehicle road navigation model may include at least one line representation of a road surface feature extending along the common road segment, and each line representation may representing a path along the common road segment substantially corresponding with the road surface feature.

Abstract: A system mounted in a vehicle for classifying light sources. The system includes a lens and a spatial image sensor. The lens is adapted to provide an image of a light source on the spatial image sensor. A diffraction grating is disposed between the lens and the light source. The diffraction grating is adapted for providing a spectrum. A processor is configured for classifying the light source as belonging to a class selected from a plurality of classes of light sources expected to be found in the vicinity of the vehicle, wherein the spectrum is used for the classifying of the light source. Both the image and the spectrum may be used for classifying the light source or the spectrum is used for classifying the light source and the image is used for another driver assistance application.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for detecting whether a road on which a host vehicle travels is a one-way road may include at least one processing device. The processing device may be programmed to receive at least one image associated with an environment of the host vehicle, identify a first plurality of vehicles on a first side of the road, identify a second plurality of vehicles on a second side of the road, determine a first facing direction associated with the first plurality of vehicles, determine a second facing direction associated with the second plurality of vehicles, and cause at least one navigational change of the host vehicle when the first facing direction and the second facing direction are both opposite to a heading direction of the host vehicle.

Abstract: Systems and methods are provided for detecting an object in front of a vehicle. In one implementation, an object detecting system includes an image capture device configured to acquire a plurality of images of an area, a data interface, and a processing device programmed to compare a first image to a second image to determine displacement vectors between pixels, to search for a region of coherent expansion that is a set of pixels in at least one of the first image and the second image, for which there exists a common focus of expansion and a common scale magnitude such that the set of pixels satisfy a relationship between pixel positions, displacement vectors, the common focus of expansion, and the common scale magnitude, and to identify presence of a substantially upright object based on the set of pixels.

Abstract: Correcting image distortion during camera motion using a system including a processor and a camera having a rolling shutter. Multiple image frames are captured by the camera equipped with the rolling shutter. The captured image frames include a base image frame and a previous image frame. Multiple time stamps are recorded respectively for multiple corresponding image points in the previous and base image frames. For the corresponding image points, multiple ego-motions are computed responsive to the time stamps of the corresponding image points of the base image frame and the previous image frame to correct the image distortion caused by the rolling shutter.

Abstract: A method is provided using a system mounted in a vehicle. The system includes a rear-viewing camera and a processor attached to the rear-viewing camera. When the driver shifts the vehicle into reverse gear, and while the vehicle is still stationary, image frames from the immediate vicinity behind the vehicle are captured. The immediate vicinity behind the vehicle is in a field of view of the rear-viewing camera. The image frames are processed and thereby the object is detected which if present in the immediate vicinity behind the vehicle would obstruct the motion of the vehicle. The processing is preferably performed in parallel for a plurality of classes of obstructing objects using a single image frame of the image frames.