Abstract: A system and method for determining when to display frontal curb view images to a driver of a vehicle, and what types of images to display. A variety of factors—such as vehicle speed, GPS/location data, the existence of a curb in forward-view images, and vehicle driving history—are evaluated as potential triggers for the curb view display, which is intended for situations where the driver is pulling the vehicle into a parking spot which is bounded in front by a curb or other structure. When forward curb-view display is triggered, a second evaluation is performed to determine what image or images to display which will provide the best view of the vehicle's position relative to the curb. The selected images are digitally synthesized or enhanced, and displayed on a console-mounted or in-dash display device.

Abstract: A system and method for providing online calibration of a plurality of cameras in a surround-view camera system on a vehicle. The method provides consecutive images from each of the cameras in the surround-view system and identifies overlap image areas for adjacent cameras. The method identifies matching feature points in the overlap areas of the images and estimates camera parameters in world coordinates for each of the cameras. The method then estimates a vehicle pose of the vehicle in world coordinates and calculates the camera parameters in vehicle coordinates using the estimated camera parameters in the world coordinates and the estimated vehicle pose to provide the calibration.

Abstract: A system and method for creating an enhanced virtual top-down view of an area in front of a vehicle, using images from left-front and right-front cameras. The enhanced virtual top-down view not only provides the driver with a top-down view perspective which is not directly available from raw camera images, but also removes the distortion and exaggerated perspective effects which are inherent in wide-angle lens images. The enhanced virtual top-down view also includes corrections for three types of problems which are typically present in de-warped images—including artificial protrusion of vehicle body parts into the image, low resolution and noise around the edges of the image, and a “double vision” effect for objects above ground level.

Abstract: A system and method for creating an enhanced perspective view of an area in front of a vehicle, using images from left-front and right-front cameras. The enhanced perspective view removes the distortion and exaggerated perspective effects which are inherent in wide-angle lens images. The enhanced perspective view uses a camera model including a virtual image surface and other processing techniques which provide corrections for two types of problems which are typically present in de-warped perspective images—including a stretching effect at the peripheral area of a wide-angle image de-warped by rectilinear projection, and double image of objects in an area where left-front and right-front camera images overlap.

Abstract: A method for adjusting a vehicle's position in a roadway lane. A camera mounted on the vehicle generates a current image of the lane and the method identifies a current lane-center line in the current image. A reference image is generated and the method identifies a reference lane-center line in the reference image. The method then calculates an error between the current lane-center line and the reference lane-center line and provide steering commands to adjust the position of the vehicle so that the error is reduced.

Abstract: A method for dynamically registering a graphic upon a cropped image obtained from a camera device includes capturing an original image obtained from the camera device. Intrinsic calibration information for the camera device, extrinsic information for the camera device and vehicle information are monitored. The cropped image is generated based on cropping parameters to exclude undesirable content from the original image. The intrinsic calibration information is adjusted based on a relationship to the cropping parameters. The graphic is dynamically registered upon the cropped image based on the adjusted intrinsic calibration information for the camera device, the monitored extrinsic information for the camera device and the monitored vehicle information.

Abstract: A method for determining a wet road surface condition for a vehicle driving on a road. A first image exterior of the vehicle is captured by an image capture device. A second image exterior of the vehicle is captured by the image capture device. A section of the road is identified in the first and second captured images. A texture of the road in the first and second images captured by a processor are compared. A determination is made whether the texture of the road in the first image is different from the texture of the road in the second image. A wet driving surface indicating signal is generated in response to the determination that the texture of the road in the first image is different than the texture of the road in the second image.

Abstract: A system and method for providing lane sensing on a vehicle by detecting roadway lane-markers, where the system employs multiple cameras providing images around the vehicle. The method includes detecting left-side and right-side lane boundary lines in the camera images, and then determining whether the lane boundary lines in the images are aligned from one image frame to a next image frame and are aligned from image to image. If the boundary lines are not aligned, then calibration of one or more of the cameras is performed, and if the lines are aligned, then a model fitting process is used to specifically identify the location of the boundary lines on the roadway.

Abstract: A system and method for providing lane sensing on a vehicle by detecting roadway lane-markers, where the system employs a surround view camera system providing a top-down view image around the vehicle. The method includes detecting left-side and right-side lane boundary lines in the top-down view image, and then determining whether the lane boundary lines in the image are aligned from one image frame to a next image frame and are aligned from image to image in the top-down view image. If the boundary lines are not aligned, then calibration of one or more of the cameras is performed, and if the lines are aligned, then a model fitting process is used to specifically identify the location of the boundary lines on the roadway.

Abstract: A vehicle obstacle detection system includes an imaging system for capturing objects in a field of view and a radar device for sensing objects in a substantially same field of view. The substantially same field of view is partitioned into an occupancy grid having a plurality of observation cells. A fusion module receives radar data from the radar device and imaging data from the imaging system. The fusion module projects the occupancy grid and associated radar data onto the captured image. The fusion module extracts features from each corresponding cell using sensor data from the radar device and imaging data from the imaging system. A primary classifier determines whether an extracted feature extracted from a respective observation cell is an obstacle.

Abstract: A method for displaying a captured image on a display device. A real image is captured by a vision-based imaging device. A virtual image is generated from the captured real image based on a mapping by a processor. The mapping utilizes a virtual camera model with a non-planar imaging surface. Projecting the virtual image formed on the non-planar image surface of the virtual camera model to the display device.

Abstract: A method for determining a wet road surface condition on a road. An image exterior of the vehicle is captured by an image capture device. A real object and a virtual object are detected in the captured image. A feature point is identified on the real object and on the virtual object. A potential virtual object associated with the real object is identified on a ground surface of the road in the captured image. The feature point detected on the real object is compared with the feature point detected on the virtual object. A determination is made whether the ground surface includes a mirror effect reflective surface in response to the feature point detected on the real object matching the feature point detected on the virtual object. A wet driving surface indicating signal is generated in response to the determination that the ground surface includes a mirror effect reflective surface.

Abstract: A method for determining a wet road surface condition for a vehicle driving on a road. A first image exterior of the vehicle is captured by an image capture device. A second image exterior of the vehicle is captured by the image capture device. A section of the road is identified in the first and second captured images. A texture of the road in the first and second images captured by a processor are compared. A determination is made whether the texture of the road in the first image is different from the texture of the road in the second image. A wet driving surface indicating signal is generated in response to the determination that the texture of the road in the first image is different than the texture of the road in the second image.

Abstract: A system and method for providing online calibration of a plurality of cameras in a surround-view camera system on a vehicle. The method provides consecutive images from each of the cameras in the surround-view system and identifies overlap image areas for adjacent cameras. The method identifies matching feature points in the overlap areas of the images and estimates camera parameters in world coordinates for each of the cameras. The method then estimates a vehicle pose of the vehicle in world coordinates and calculates the camera parameters in vehicle coordinates using the estimated camera parameters in the world coordinates and the estimated vehicle pose to provide the calibration.

Abstract: A lane controller system installed on a vehicle may include components for self-diagnosing malfunctions on the vehicle. The system may include a desired path generator for generating a desired path that keeps the vehicle within a road lane; a steering controller for providing steering a steering correction to keep the vehicle within the road lane; a vehicle state estimator for estimating the state of the vehicle; a lane marking detector for detecting position of road lane markings; a path predictor for predicting a path actively followed by the vehicle; a virtual dynamics module for modeling the anticipated path of the vehicle following input of the steering controller; a comparer that compares the results of actual steering corrections applied with those predicted by the virtual dynamics module, and a diagnostic system that determines a root cause of malfunctions, based on the comparison by the comparer.

Abstract: In one embodiment, a system and method may collect acceleration data for a driver for a vehicle, compare the acceleration data for the driver to a set of acceleration data representing a plurality of sample drivers driving in the same type of vehicle as the vehicle, and based on the comparison, determining a driving style rating for the driver.

Abstract: A method and system for estimating the state of health of an object sensing fusion system. Target data from a vision system and a radar system, which are used by an object sensing fusion system, are also stored in a context queue. The context queue maintains the vision and radar target data for a sequence of many frames covering a sliding window of time. The target data from the context queue are used to compute matching scores, which are indicative of how well vision targets correlate with radar targets, and vice versa. The matching scores are computed within individual frames of vision and radar data, and across a sequence of multiple frames. The matching scores are used to assess the state of health of the object sensing fusion system. If the fusion system state of health is below a certain threshold, one or more faulty sensors are identified.

Abstract: A method of determining a road surface condition for a vehicle driving on a road. Probabilities associated with a plurality of road surface conditions based on an image of a capture scene are determined by a first probability module. Probabilities associated with the plurality of road surface conditions based on vehicle operating data are determined by a second probability module. The probabilities determined by the first and second probability modules are input to a data fusion unit for fusing the probabilities and determining a road surface condition. A refined probability is output from the data fusion unit that is a function of the fused first and second probabilities. The refined probability from the data fusion unit is provided to an adaptive learning unit. The adaptive learning unit generates output commands that refine tunable parameters of at least the first probability and second probability modules for determining the respective probabilities.

Abstract: A lane tracking system for tracking the position of a vehicle within a lane includes a camera configured to provide a video feed representative of a field of view and a video processor configured to receive the video feed from the camera and to generate latent video-based position data indicative of the position of the vehicle within the lane. The system further includes a vehicle motion sensor configured to generate vehicle motion data indicative of the motion of the vehicle, and a lane tracking processor. The lane tracking processor is configured to receive the video-based position data, updated at a first frequency; receive the sensed vehicle motion data, updated at a second frequency; estimate the position of the vehicle within the lane from the sensed vehicle motion data; and fuse the video-based position data with the estimate of the vehicle position within the lane using a Kalman filter.

Abstract: A method for determining a wet road surface condition for a vehicle driving on a road. An image exterior of the vehicle is captured by an image capture device at a first and second instance of time. Potential objects and feature objects are detected on a ground surface of the road of travel at the first instance of time and the second instance of time. A determination is made whether the ground surface includes a mirror effect reflective surface based on a triangulation technique utilizing the feature points in the captured images at the first instance of time and the second instance of time. A wet driving surface indicating signal is generated in response to the determination that the ground surface includes a mirror effect reflective surface.