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: Various driver assistance systems mountable in a host vehicle and computerized methods for detecting a vertical deviation of a road surface. The driver assistance system includes a camera operatively connectible to a processor. Multiple consecutive image frames are captured from the camera including a first image of the road and a second image of the road. Based on the host vehicle motion, the second image is warped toward the first image to produce thereby a warped second image. Image points of the road in the first image and corresponding image points of the road in the warped second image are tracked. Optical flow is computed between the warped second image to the first image. The optical flow is compared with an optical flow based on a road surface model to produce a residual optical flow. The vertical deviation is computed from the residual optical flow.

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: A vehicle navigation system may comprise a memory including instructions and circuitry configured by the instructions to identify a target vehicle in an environment of a vehicle that includes the vehicle navigation system. The circuitry may receive image data of the target vehicle from at least one image capture device of the vehicle; identify, based on analysis of the image data, one or more situational characteristics of the target vehicle, the situational characteristics of the target including an indication that the target vehicle has an activated blinker; and change a navigational state of the vehicle to allow an action of the target vehicle. The vehicle may be configured to cause the change in the navigational state based on a determination that the one or more situational characteristics, including the activated blinker, indicate that the target vehicle would benefit from the change in the navigational state.

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.

Abstract: A camera and production technique for an ADAS. The camera lens and image sensor are positioned along multiple axes using a target located at a first distance from the lens to establish a first relative position between the lens and the image sensor. The first relative position between the lens and the image sensor is modified by a predetermined amount for an object located a second distance from the lens. The second distance is larger than the first distance.

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

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

Abstract: Detection of three dimensional obstacles using a system mountable in a host vehicle including a camera connectible to a processor. Multiple image frames are captured in the field of view of the camera. In the image frames, an imaged feature is detected of an object in the environment of the vehicle. The image frames are portioned locally around the imaged feature to produce imaged portions of the image frames including the imaged feature. The image frames are processed to compute a depth map locally around the detected imaged feature in the image portions. Responsive to the depth map, it is determined if the object is an obstacle to the motion of the vehicle.

Abstract: A system mountable in a vehicle to provide object detection in the vicinity of the vehicle. The system includes a camera operatively attached to a processor. The camera is mounted externally at the rear of the vehicle. The field of view of the camera is substantially in the forward direction of travel of the vehicle along the side of the vehicle. Multiple image frames are captured from the camera. Yaw of the vehicle may be input or the yaw may be computed from the image frames. Respective portions of the image frames are selected responsive to the yaw of the vehicle. The image frames are processed to detect thereby an object in the selected portions of the image frames.

Abstract: Driver assistance systems for detecting a structural barrier extending along a road. The driver assistance system may be mountable in a host vehicle. The camera may capture multiple image frames in the forward field of view of the camera. A processor may process motion of images of the barrier in the image frames. The camera may be a single camera. The motion of the images may be responsive to forward motion of the host vehicle and/or the motion of the images may be responsive to lateral motion of the host vehicle.

Abstract: An imaging system for a vehicle may include a first image capture device having a first field of view and configured to acquire a first image relative to a scene associated with the vehicle, the first image being acquired as a first series of image scan lines captured using a rolling shutter. The imaging system may also include a second image capture device having a second field of view different from the first field of view and that at least partially overlaps the first field of view, the second image capture device being configured to acquire a second image relative to the scene associated with the vehicle, the second image being acquired as a second series of image scan lines captured using a rolling shutter. As a result of overlap between the first field of view and the second field of view, a first overlap portion of the first image corresponds with a second overlap portion of the second image.

Abstract: Determining three-dimensional structure in a road environment using a system mountable in a host vehicle including a camera connectible to a processor. Multiple image frames are captured in the field of view of the camera. In the image frames, a line is selected below which the road is imaged. The line separates between upper images essentially excluding images of the road and lower images essentially including images of the road. One or more of the lower images is warped, according to a road homography to produce at least one warped lower image. The three-dimensional structure may be provided from motion of a matching feature within the upper images or from motion of a matching feature within at least one of the lower images and at least one warped lower image.

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 control system for a vehicle may include a forward-facing camera to capture a plurality of images of a road ahead of the vehicle and a processing device. The processing device may be configured to: provide feedback to a vehicle operator of the vehicle to change lanes to a new lane, in which the vehicle is not already traveling, based on the ending of a current lane, the ending of the current lane indicated by a first traffic cone identified in the plurality of images; and update a distance from the vehicle to a second traffic cone, based on a position of the vehicle, the second traffic cone used to constrain vehicle operation to the new lane.

Abstract: Systems and methods are provided for determining a road surface characteristic. In one implementation, a system includes at least one processing device programmed to receive, from at least one camera, at least two images representative of an environment of a vehicle; align at least a portion of the at least two images using estimated motion of the vehicle; provide, to a trained system configured to determine a characteristic of the road surface, at least the aligned portions of the at least two images; receive, from the trained system, the determined characteristic of the road surface; and provide, to a vehicle control system, based on at least the determined characteristic of the road surface, control information for changing at least one setting of the vehicle control system.

Abstract: A system mountable in a vehicle to provide object detection in the vicinity of the vehicle. The system includes a camera operatively attached to a processor. The camera is mounted externally at the rear of the vehicle. The field of view of the camera is substantially in the forward direction of travel of the vehicle along the side of the vehicle. Multiple image frames are captured from the camera. Yaw of the vehicle may be input or the yaw may be computed from the image frames. Respective portions of the image frames are selected responsive to the yaw of the vehicle. The image frames are processed to detect thereby an object in the selected portions of the image frames.

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

Abstract: A driver assistance systems mountable in a host vehicle while the host vehicle is moving forward with headlights on for detection of obstacles based on shadows. The driver assistance system includes a camera operatively connectible to a processor. A first image frame and a second image frame are captured of a road. A first dark image patch and a second dark image patch include intensity values less than a threshold value. The first and the second dark image patches are tracked from the first image frame to the second image frame as corresponding images of the same portion of the road. Respective thicknesses in vertical image coordinates are measured of the first and second dark image patches responsive to the tracking.