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; analyze the plurality of images to identify a first flow of traffic and a second flow of traffic; determine a presence of at least one navigational state characteristic indicative of an alternating merging of the first flow of traffic and the second flow of traffic into a merged lane; cause at least a first navigational change to allow one target vehicle from the first flow of traffic to proceed ahead of the host vehicle; and cause at least a second navigational change to cause the host vehicle to follow the target vehicle into the merged lane.

Abstract: Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a system for navigating a vehicle includes at least one processing device programmed to receive, from an image capture device, a plurality of images associated with an environment of the vehicle, analyze at least one of the plurality of images to identify a navigable region in the environment of the vehicle, identify, based on the at least one of the plurality of images, at least one barrier associated with an edge of the navigable region, and determine a type of the at least one barrier. The at least one processing device is also programmed to determine a navigational path of the vehicle based on the determined type of the at least one barrier, and cause the vehicle to travel on at least a portion of the determined navigational path.

Abstract: A camera mount for mounting a camera inside a windshield of a vehicle. The camera includes a lens mount and a camera housing. The front tip of the lens mount is constrained to be in close proximity to or constrained to contact the inside of the windshield for different rake angles of the windshield.

Abstract: A system and method estimate a future path ahead of a current location of a vehicle. The system includes at least one processor programmed to obtain a trained system that was trained to estimate a future path on a first plurality of images of environments ahead of vehicles navigating roads. The at least one processor is also programmed to obtain an image of an environment ahead of a current arbitrary location of a vehicle navigating a road, and provide, based on an application of the trained system to the obtained image, an estimated future path of the vehicle ahead of the current arbitrary location.

Abstract: A camera system including: an image sensor that is controlled by one or more camera parameters; and a pre-processing circuit adapted to associate weights respectively with cells of a grid, wherein the weights differ from the one or more camera parameters, wherein the cells respectively include a plurality of contiguous picture elements of the image sensor.

Abstract: A method for error correction and a system. The method may include opening a selected row of a memory bank out of multiple memory banks of a dynamic memory module; and while the selected row is open: (i) receiving selected data sub-blocks that are targeted to be written to the selected row, (ii) calculating selected error correction code sub-blocks that are related to the selected data sub-blocks, (iii) caching the selected error correction code sub-blocks in a cache memory that differs from the dynamic memory module and (iv) writing, to the selected row, the selected error correction code sub-blocks.

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: A detection system for a vehicle is provided. The detection system may include at least one image capture device configured to acquire a plurality of images of an area forward of the vehicle, the area including a curb separating a road surface from an off-road surface and a data interface. The detection system may also include at least one processing device programmed to receive the plurality of images via the data interface, and determine a plurality of curb edge line candidates in the plurality of images. The at least one processing device may be further programmed to identify at least one edge line candidate as an edge line of the curb.

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 a host vehicle, wherein at least one of the outputs is received from a sensor onboard the host vehicle. The processing device may identify a target object in the first output and determine whether a characteristic of the target object triggers a navigational constraint by verifying the identification of the target object based on the first output; and, if the navigational constraint is not verified based on the first output, then verifying the identification of the target object based on a combination of the first output and the second output. In response to the verification, the processing device may cause at least one navigational change to the host vehicle.

Abstract: Systems and methods are disclosed for navigating a host vehicle. In one implementation, at least one processor may be programmed to obtain images representative of an environment of a host vehicle; identify, from the images, a feature of a roadway used to navigate the host vehicle on a path, the identified feature of the roadway having an ambiguity along the path; obtain map data associated with the environment to resolve the ambiguity of the identified feature; and generate a trajectory to navigate the host vehicle on the roadway, using the map data associated with the environment.

Abstract: Systems and methods are provided for navigating a host vehicle. In some embodiments, the system may include at least one processing device programmed to: receive at least one image representative of an environment of the host vehicle; determine a navigational action of the host vehicle; analyze the at least one 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 implement the navigational action if the determined stopping distance for the host vehicle is less than the next-state distance summed with a target vehicle travel distance.

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 crowdsourcing road surface information collection. In one implementation, a method of collecting road surface information for a road segment may include receiving at least one image representative of a portion of the road segment, identifying in the at least one image at least one road surface feature along the portion of the road segment, determining a plurality of locations associated with the road surface feature according to a local coordinate system of the vehicle, and transmitting the determined plurality of locations from the vehicle to a server. The determined locations may be configured to enable determination by the server of a line representation of the road surface feature extending along the road segment.

Abstract: Systems and methods are provided for detecting an object and causing a vehicle to brake based on the detection. In one implementation, an object detecting and braking system for a vehicle includes at least one image capture device configured to acquire a plurality of images of an area including an object in front of the vehicle. The system includes at least one processing device programmed to perform a first image analysis to determine a first estimated time-to-collision of the vehicle with the object, and to perform a second image analysis to determine a second estimated time-to-collision of the vehicle with the object. The processing device is also programmed to calculate a difference between the first estimated time-to-collision and the second estimated time-to-collision, to determine that the difference does not exceed a predetermined threshold, and to cause the vehicle to brake based on the determination that the difference does not exceed the predetermined threshold.

Abstract: A system for mapping traffic lights and for determining traffic light relevancy for use in autonomous vehicle navigation. The system may include at least one processor programmed to: receive at least one location identifier associated with a traffic light; receive a state identifier associated with the traffic light; receive navigational information indicative of one or more aspects of motion of the first vehicle along the road segment, and determine, based on the navigational information, a lane of travel traversed by the first vehicle along the road segment. The processor may also determine whether the traffic light is relevant to the lane of travel traversed by the first vehicle; update an autonomous vehicle road navigation model relative to the road segment; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

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: A system for mapping traffic lights and associated traffic light cycle times for use in autonomous vehicle navigation. The system includes at least one processor programmed to: receive at least one location identifier associated with a traffic light detected along a road segment; receive at least one indicator of traffic light state timing associated with the detected traffic light; and update an autonomous vehicle road navigation model relative to the road segment. The update can be based on the at least one location identifier and based on the at least one indicator of traffic light state timing associated with the traffic light detected along the road segment. The processor may also include distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Abstract: A system for mapping road segment free spaces for use in autonomous vehicle navigation. The system includes at least one processor programmed to: receive from a first vehicle one or more location identifiers associated with a lateral region of free space adjacent to a road segment; update an autonomous vehicle road navigation model for the road segment to include a mapped representation of the lateral region of free space based on the received one or more location identifiers; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

Abstract: A navigation system includes a processing device programmed to receive, from an image capture device, at least one image of an environment of the host vehicle; determine, based on at least one driving policy, a navigational action for accomplishing a navigational goal of the host vehicle; analyze the at least one image to identify a target vehicle; test the navigational action against at least one accident liability rule for determining potential accident liability for the host vehicle relative to the target vehicle; if the test indicates that potential accident liability exists for the host vehicle if the navigational action is taken, then cause the host vehicle not to implement the navigational action; and if the test indicates that no accident liability would result for the host vehicle if the navigational action is taken, then cause the host vehicle to implement the navigational action.