Abstract: A method of identifying a condition of a road surface includes capturing at least a first image of the road surface with a first camera, and a second image of the road surface with a second camera. The first image and the second image are tiled together to form a combined tile image. A feature vector is extracted from the combined tile image using a convolutional neural network, and a condition of the road surface is determined from the feature vector using a classifier.

Abstract: Technical solutions are described for controlling an automated driving system of a vehicle. An example method includes computing a complexity metric of an upcoming region along a route that the vehicle is traveling along. The method further includes, in response to the complexity metric being below a predetermined low-complexity threshold, determining a trajectory for the vehicle to travel in the upcoming region using a computing system of the vehicle. Further, the method includes in response to the complexity metric being above a predetermined high-complexity threshold, instructing an external computing system to determine the trajectory for the vehicle to travel in the upcoming region. If the trajectory cannot be determined by the external computing system a minimal risk condition maneuver of the vehicle is performed.

Abstract: A system and method to perform dynamic bandwidth adjustment among two or more vehicle sensors includes receiving input. The input includes data from each of the two or more vehicle sensors. The two or more vehicle sensors include a camera, an audio detector, a radar system, or a lidar system. The method also includes determining a bandwidth at which each of the two or more vehicle sensors should provide the data, and providing a control signal to each of the two or more vehicle sensors to adjust the bandwidth based on the determining.

Abstract: A system and method for generating a range image using sparse depth data is disclosed. The method includes receiving, by a controller, image data of a scene. The image data includes a first set of pixels. The method also includes receiving, by the controller, a sparse depth data of the scene. The sparse depth data includes a second set of pixels, and the number of the second set of pixels is less than the number of first set of pixels. The method also includes combining the image data and the sparse depth data into a combined data. The method also includes generating a range image using the combined data.

Abstract: A method and apparatus for determining ground clearance of a structure are provided. The method includes removing reflection points caused by noise from first reflection point information based on temporal persistency and generating second reflection point information, extracting visual features from an image of a camera based on convolutional neural network, projecting the second reflection point information onto the image, generating region proposals based on the projected second reflection point information and the image, the region proposals indicating potential horizontal structures above a path, detecting stationary horizontal structure above a path based on the generated region proposals, and determining distance between ground and the detected stationary horizontal structure based on the projected reflection point information and the image.

Abstract: A method and apparatus for trailer recognition are provided. The method includes detecting a face of a trailer in a first and second image, taken at first and second distances respectively, generating a bounding box around the face of the trailer in the first and second images, determining a first and second set of feature points in the bounding boxes of the first and second images, determining a correspondence between the first set of feature points and the second set of feature points and a correspondence between corners of the bounding boxes and estimating at least one dimension of the trailer by performing a least squares analysis to solve for three-dimensional real world coordinates of the first and second set of features points and the corners of the bounding boxes. The method may assist an operator of a vehicle in aligning the vehicle hitch with a trailer coupler.

Abstract: A system and method are provided for detecting and identifying elongated objects relative to a host vehicle. The method includes detecting objects relative to the host vehicle using a plurality of object detection devices, identifying patterns in detection data that correspond to an elongated object, wherein the detection data includes data fused from at least two of the plurality of object detection devices, determining initial object parameter estimates for the elongated object using each of the plurality of object detection devices, calculating object parameter estimates for the elongated object by fusing the initial object parameter estimates from each of the plurality of object detection devices, and determining an object type classification for the elongated object by fusing the initial object parameter estimates from each of the plurality of object detection devices.

Abstract: An adaptive parallel imaging processing system in a vehicle is provided.

Abstract: An ajar tailgate detection system for a vehicle having a parking assist system and a method for controlling the same are provided. The ajar tailgate detection system may include, but not limited to, a camera configured to output image data and a processor communicatively coupled to the camera and the parking assist system, the processor configured to determine when the tailgate is open based upon the image data output from the camera generate, when the tailgate is determined to be open, one of instructions to load a tailgate ajar calibration file into the parking assist system or instructions to disable the parking assist system, the tailgate ajar calibration file defining a second vehicle length and defining a second data acquisition range of the at least one sensor and transmit the generated instructions to the parking assist system.

Abstract: Technical solutions are described for vehicle collision prevention for a vehicle when the vehicle is in a parked condition. An example method includes performing a stationary safety monitoring when the vehicle is in parked condition. The stationary safety monitoring includes detecting presence of a moving object within a predetermined region from the vehicle. Further, the method includes, in response to detecting the moving object in the predetermined region initiating a notification for the moving object to prevent collision with the vehicle.

Abstract: Methods and systems are provided for determining a vehicle position. In one embodiment, a method includes: receiving, by a processor of a rover vehicle, vehicle position data from one or more parked vehicles; receiving, by the processor of the rover vehicle, global positioning system data from a GPS receiver of the rover vehicle; and processing, by the processor of the rover vehicle, the vehicle position data and the global position system data to determine a position of the rover vehicle.

Abstract: A vehicle, system and method of driving of an autonomous vehicle. The vehicle includes a camera for obtaining an image of a surrounding region of the vehicle, an actuation device for controlling a parameter of motion of the vehicle, and a processor. The processor selects a context region within the image, wherein the context region including a detection region therein. The processor further estimates a confidence level indicative of the presence of at least a portion of the target object in the detection region and a bounding box associated with the target object, determines a proposal region from the bounding box when the confidence level is greater than a selected threshold, determines a parameter of the target object within the proposal region, and controls the actuation device to alter a parameter of motion of the vehicle based on the parameter of the target object.

Abstract: Methods and apparatus are provided for cleaning a sensor lens cover for an optical vehicle sensor. The method includes monitoring the sensor lens cover for a contaminant obstructing at least a portion of the sensor lens cover and determining the presence of the commandant and a contaminant type using information provided by one or more vehicle sensors. A cleaning modality selected based the contaminant type is activated and it is determined whether the cleaning modality has removed the contaminant from the sensor lens cover.

Abstract: An autonomic vehicle control system is described, and includes a vehicle spatial monitoring system including a subject spatial sensor that is disposed to monitor a spatial environment proximal to the autonomous vehicle. A controller is in communication with the subject spatial sensor, and the controller includes a processor and a memory device including an instruction set. The instruction set is executable to evaluate the subject spatial sensor, which includes determining first, second, third, fourth and fifth SOH (state of health) parameters associated with the subject spatial sensor, and determining an integrated SOH parameter for the subject spatial sensor based thereupon.

Abstract: A vehicle, system and method of driving of an autonomous vehicle. The vehicle includes a camera for obtaining an image of a surrounding region of the vehicle, an actuation device for controlling a parameter of motion of the vehicle, and a processor. The processor selects a context region within the image, wherein the context region including a detection region therein. The processor further estimates a confidence level indicative of the presence of at least a portion of the target object in the detection region and a bounding box associated with the target object, determines a proposal region from the bounding box when the confidence level is greater than a selected threshold, determines a parameter of the target object within the proposal region, and controls the actuation device to alter a parameter of motion of the vehicle based on the parameter of the target object.

Abstract: An autonomic vehicle control system includes a perception module of a spatial monitoring system that is disposed to monitor a spatial environment proximal to the autonomous vehicle. A method for evaluating vehicle dynamics operation includes determining a desired trajectory for the autonomous vehicle, wherein the desired trajectory includes desired vehicle positions including an x-position, a y-position and a heading. Vehicle control commands are determined based upon the desired trajectory, and include a commanded steering angle, an acceleration command and a braking command. Actual vehicle states responsive to the vehicle control commands are determined. An estimated trajectory is determined based upon the actual vehicle states, and a trajectory error is determined based upon a difference between the desired trajectory and the estimated trajectory. The trajectory error is monitored over a time horizon, and a first state of health (SOH) is determined based upon the trajectory error over the time horizon.

Abstract: A system and method to fuse a radar system and a vision sensor system include obtaining radar reflections resulting from transmissions of radio frequency (RF) energy. The method includes obtaining image frames from one or more vision sensor systems, and generating region of interest (ROI) proposals based on the radar reflections and the image frames. Information is provided about objects detected based on the ROI proposals.

Abstract: A method of identifying a condition of a road surface includes capturing at least a first image of the road surface with a first camera, and a second image of the road surface with a second camera. The first image and the second image are tiled together to form a combined tile image. A feature vector is extracted from the combined tile image using a convolutional neural network, and a condition of the road surface is determined from the feature vector using a classifier.

Abstract: A method and apparatus for determining ground clearance of a structure are provided. The method includes removing reflection points caused by noise from first reflection point information based on temporal persistency and generating second reflection point information, extracting visual features from an image of a camera based on convolutional neural network, projecting the second reflection point information onto the image, generating region proposals based on the projected second reflection point information and the image, the region proposals indicating potential horizontal structures above a path, detecting stationary horizontal structure above a path based on the generated region proposals, and determining distance between ground and the detected stationary horizontal structure based on the projected reflection point information and the image.

Abstract: Methods and apparatus are provided for controlling an autonomous vehicle. A sensor fusion system with a sensor system for providing environment condition information and a convolutional neural network (CNN) is provided. The CNN includes a receiving interface configured to receive the environment condition information from the sensor system, a common convolutional layer configured to extract traffic information from the received environment condition information, and a plurality of fully connected layers configured to detect objects belonging to different object classes based on the extracted traffic information, wherein the object classes include at least one of a road feature class, a static object class, and a dynamic object class.