Abstract: Determining three-dimensional structure in a road environment using a system mountable in a host vehicle including a camera connectable 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: A navigation system may include at least one processing device configured to determine, based on an output of one or more position sensors associated with the navigation system, a current location of at least one component associated with the navigation system and determine a destination location different from the current location. The navigation system may also acquire, from one or more image acquisition devices, a plurality of images representative of an environment of a user of the navigation system and derive, from the plurality of images, visual information associated with at least one object in the environment. The system may also determine one or more instructions for navigating from the current location to the destination location, wherein the one or more instructions include at least one reference to the visual information derived from the plurality of images. The system may also deliver to the user the one or more instructions.

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

Abstract: Systems and methods are provided for detecting and responding to cut in vehicles, and for navigating while taking into consideration an altruistic behavior parameter. In one implementation, a vehicle cut in detection and response system for a host vehicle system may include a data interface and at least one processing device.

Abstract: A system mounted on a vehicle for detecting an obstruction on a surface of a window of the vehicle, a primary camera is mounted inside the vehicle behind the window. The primary camera is configured to acquire images of the environment through the window. A secondary camera is focused on an external surface of the window, and operates to image the obstruction. A portion of the window, i.e. window region is subtended respectively by the field of view of the primary camera and the field of view of the secondary camera. A processor processes respective sequences of image data from both the primary camera and the secondary camera.

Abstract: A system for navigating an autonomous vehicle using reinforcement learning techniques is provided. The system includes at least one processing device programmed to: receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a present navigational state associated with the host vehicle; select a second potential navigational action based on a determination that an expected reward associated with a fourth indicator is greater than an expected reward associated with a second indicator.

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: 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: 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 are provided for navigating an autonomous vehicle using reinforcement learning techniques.

Abstract: A method of estimating a time to collision (TTC) of a vehicle with an object comprising: acquiring a plurality of images of the object; and determining a TTC from the images that is responsive to a relative velocity and relative acceleration between the vehicle and the object.

Abstract: A system mounted on a vehicle for detecting an obstruction on a surface of a window of the vehicle, a primary camera is mounted inside the vehicle behind the window. The primary camera is configured to acquire images of the environment through the window. A secondary camera is focused on an external surface of the window, and operates to image the obstruction. A portion of the window, i.e. window region is subtended respectively by the field of view of the primary camera and the field of view of the secondary camera. A processor processes respective sequences of image data from both the primary camera and the secondary camera.

Abstract: Systems and methods are provided for determining a road profile along a predicted path. In one implementation, a system includes at least one image capture device configured to acquire a plurality of images of an area in a vicinity of a user vehicle; a data interface; and at least one processing device configured to receive the plurality of images captured by the image capture device through the data interface; and compute a profile of a road along one or more predicted paths of the user vehicle. At least one of the one or more predicted paths is predicted based on image data.

Abstract: A navigation system may include at least one processing device configured to determine, based on an output of one or more position sensors associated with the navigation system, a current location of at least one component associated with the navigation system and determine a destination location different from the current location. The navigation system may also acquire, from one or more image acquisition devices, a plurality of images representative of an environment of a user of the navigation system and derive, from the plurality of images, visual information associated with at least one object in the environment. The system may also determine one or more instructions for navigating from the current location to the destination location, wherein the one or more instructions include at least one reference to the visual information derived from the plurality of images. The system may also deliver to the user the one or more instructions.

Abstract: A method is provided for preventing a collision between a motor vehicle and a pedestrian. The method uses a camera and a processor mountable in the motor vehicle. A candidate image is detected. Based on a change of scale of the candidate image, it may be determined that the motor vehicle and the pedestrian are expected to collide, thereby producing a potential collision warning. Further information from the image frames may be used to validate the potential collision warning. The validation may include an analysis of the optical flow of the candidate image, that lane markings prediction of a straight road, a calculation of the lateral motion of the pedestrian, if the pedestrian is crossing a lane mark or curb and/or if the vehicle is changing lanes.

Abstract: Systems and methods are provided for determining a road profile along a predicted path. In one implementation, a system includes at least one image capture device configured to acquire a plurality of images of an area in a vicinity of a user vehicle; a data interface; and at least one processing device configured to receive the plurality of images captured by the image capture device through the data interface; and compute a profile of a road along one or more predicted paths of the user vehicle. At least one of the one or more predicted paths is predicted based on image data.

Abstract: A navigation system for a host vehicle is provided. The system may comprise at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a navigational state associated with the host vehicle; determine a first predefined navigational constraint implicated by at least one aspect of the navigational state; identify, based on analysis of the plurality of images, a presence of at least one navigational constraint augmentation factor; determine a second navigational constraint based on identification of the at least one navigational constraint augmentation factor; determine, based on the identified navigational state, a navigational action for the host vehicle satisfying the second navigational constraint; and cause at least one adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.

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 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: Systems and methods for navigating a host vehicle. The system may perform operations comprising receiving, from an image capture device, a plurality of images representative of an environment of the host vehicle; analyzing at least one of the plurality of images to identify a first object in the environment of the vehicle, wherein the first object and a road on which the first object is located are at least partially obscured by a second object in the environment of the vehicle; determining scale change information for the first object based on at least two of the plurality of images; determining, based on the determined scale change information for the first object, a lane position of the first object relative to a lane of the road on which the first object is located; and determining a navigational action for the host vehicle based on the determined lane position.