Abstract: A vehicle system configured to control a trailer alignment routine comprises a hitch mounted on a vehicle and a controller. The controller is configured to identify a coupler position of a trailer and control motion of the vehicle to toward an aligned position. The controller is further configured to control a braking procedure of the vehicle comprising a plurality of concurrent deceleration control procedures in response to a portion of the vehicle passing a gradual stopping distance. The concurrent deceleration procedures comprise monitoring an elapsed time following the portion of the vehicle passing the gradual stopping distance and monitoring a remaining distance to the aligned position based on a velocity of the vehicle and comparing the remaining distance to a rapid stopping distance.

Abstract: A hitch assist system for a vehicle comprises an imaging system that receives image data of a hitch ball and trailer coupler, and a controller. The controller estimates a distance between a point on each of the hitch ball and trailer coupler. The points are parallel to a plane defined by a surface beneath the hitch ball and trailer coupler. The controller tracks the distance with a pixel-domain comparison between each of the points responsive to the distance being less than a first threshold, and maneuvers, via steering and braking systems, the vehicle along a path such that the distance is indicative of the points being coaxial.

Abstract: A system for assisting in aligning a vehicle for hitching with a trailer includes a vehicle steering system, a detection system outputting a signal including object position information of an area to a rear of the vehicle, and a controller. The controller receiving the object position data and identifying a targeted trailer and at least one additional object within the area to the rear of the vehicle and controlling the vehicle steering system to maneuver the vehicle during reversing to align a hitch ball mounted on the vehicle to a coupler of the targeted trailer. Upon aligning the hitch ball with the coupler, the controller presents an indication, if it is determined that the at least one additional object is within a threshold distance of a side of the targeted trailer.

Abstract: A system for assisting in aligning a vehicle for hitching with a trailer includes a vehicle steering system, an imager mounted with and directed to a rear of the vehicle and outputting image data, and a controller. The controller receives the image data, applies a location identifier of a vehicle hitch ball to the image data, and identifies a coupler of the trailer within the image data. The controller also outputs a steering control signal to the steering system in reversing of the vehicle to align the location identifier of the vehicle hitch ball in the image data with the coupler of the trailer.

Abstract: A computer includes a processor and a memory, the memory storing instructions executable by the processor to collect a plurality of images of one or more targets at an intersection, input the images to a machine learning program to determine a number of the targets to which a host vehicle is predicted to yield at the intersection based on time differences between the plurality of images, and transmit a message indicating the number of the targets.

Abstract: A vehicle control system includes an imager mounted with and directed to a rear of the vehicle and outputting image data, a vehicle speed sensor mounted with the vehicle and outputting vehicle speed data, and an image processor receiving the image data and the vehicle speed data. The image processor is programmed to monitor a signal from the vehicle speed sensor and, when the signal from the vehicle speed sensor indicates a vehicle speed above a predetermined minimum speed, execute a feature extraction function to locate a hitch ball mounted to the vehicle in the image data.

Abstract: A vehicle control system includes an imager mounted with and directed to a rear of the vehicle and outputting image data, a vehicle speed sensor mounted with the vehicle and outputting vehicle speed data, and an image processor receiving the image data and the vehicle speed data. The image processor is programmed to monitor a signal from the vehicle speed sensor and, when the signal from the vehicle speed sensor indicates a vehicle speed above a predetermined minimum speed, execute a feature extraction function to locate a hitch ball mounted to the vehicle in the image data.

Abstract: A vehicle maneuvering system comprises at least one image device configured to capture image data and a controller. The controller is configured to identify a coupler position of a trailer in the image data and control motion of the vehicle navigating a hitch ball of the vehicle toward the coupler position. The controller is further configured to monitor a coupler distance extending from the coupler position and the hitch ball. In response to the coupler distance being less than or equal to the distance threshold, the controller is configured to classify a plurality of portions of the image data as trailer portions and non-trailer portions and identify the coupler position by processing the image via a feature extraction operation.

Abstract: A hitch assist system is provided herein that includes a sensing system configured to detect a trailer proximate a vehicle. The hitch assist system also includes a controller for detecting a coupler of the trailer; determining a trailer-heading direction-based on a coupler orientation; and determining a path for aligning a hitch assembly on the vehicle with a coupler on the trailer based on the trailer-heading direction.

Abstract: A hitch assist system is provided herein that includes a sensing system configured to detect a trailer proximate a vehicle. The hitch assist system also includes a controller for detecting a coupler of the trailer; determining a trailer-heading direction-based on a coupler orientation; and determining a path for aligning a hitch assembly on the vehicle with a coupler on the trailer based on the trailer-heading direction.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to perform visual odometry using a monocular camera. An example apparatus includes a method fusioner to determine a visual odometry method using a surface characterization to calculate first odometry data, a displacement determiner to calculate second odometry data based on sensor information, an odometry calculator to calculate an odometry parameter of a target object with respect to a vehicle based on the first and the second odometry data, and a vehicle command generator to generate a vehicle command based on the odometry parameter.

Abstract: Techniques pertaining to vehicle occupancy indication and utilization thereof are described. A method may involve determining occupancy information regarding a number of occupants in a vehicle. The method may also involve indicating the occupancy information in either or both of a human-perceivable way and a machine-perceivable way.

Abstract: A vehicle is disclosed that uses data from different types of on-board sensors to determine whether meteorological precipitation is failing near the vehicle. The vehicle may include an on-board camera capturing image data and an on-board accelerometer capturing accelerometer data. The image data may characterize an area in front of or behind the vehicle. The accelerometer data may characterize vibrations of a windshield of the vehicle. An artificial neural network may run on computer hardware carried on-board the vehicle. The artificial neural network may be trained to classify meteorological precipitation in an environment of the vehicle using the image data and the accelerometer data as inputs. The classifications of the artificial neural network may be used to control one or more functions of the vehicle such as windshield-wiper speed, traction-control settings, or the like.

Abstract: The present invention extends to methods, systems, and computer program products for using Unmanned Aerial Vehicles (UAVs) to inspect autonomous vehicles. An autonomous vehicle carries a UAV (or “drone”) in a protected area, for example, in a glove compartment, trunk, etc. Between rides, the UAV can be deployed to inspect the autonomous vehicle. Images from the UAV can be sent to other components for image analysis. When an inspection is completed, the UAV can return to the protected area. The UAV can inspect both the interior and exterior of an autonomous vehicle. When an inspection is passed, the autonomous vehicle can begin a new ride. When an inspection is failed, the autonomous vehicle can report for repairs or summon a tow vehicle.

Abstract: Techniques pertaining to vehicle occupancy indication and utilization thereof are described. A method may involve determining occupancy information regarding a number of occupants in a vehicle. The method may also involve indicating the occupancy information in either or both of a human-perceivable way and a machine-perceivable way.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to perform visual odometry using a monocular camera. An example apparatus includes a method fusioner to determine a visual odometry method using a surface characterization to calculate first odometry data, a displacement determiner to calculate second odometry data based on sensor information, an odometry calculator to calculate an odometry parameter of a target object with respect to a vehicle based on the first and the second odometry data, and a vehicle command generator to generate a vehicle command based on the odometry parameter.

Abstract: Example accident attenuation systems and methods are described. In one implementation, a method determines a speed of a second vehicle approaching from behind a first vehicle and determines a distance between the first and second vehicles. The method also determines whether the second vehicle can stop before colliding with the first vehicle. If the second vehicle cannot stop before colliding with the first vehicle, the method takes action to attenuate the potential collision by applying full brake force, tightening seat belts, and/or turning the front wheels of the first vehicle to direct the first vehicle away from oncoming traffic.

Abstract: Techniques pertaining to vehicle occupancy indication and utilization thereof are described. A method may involve determining occupancy information regarding a number of occupants in a vehicle. The method may also involve indicating the occupancy information in either or both of a human-perceivable way and a machine-perceivable way.

Abstract: A vehicle is disclosed that uses data from different types of on-board sensors to determine whether meteorological precipitation is failing near the vehicle. The vehicle may include an on-board camera capturing image data and an on-board accelerometer capturing accelerometer data. The image data may characterize an area in front of or behind the vehicle. The accelerometer data may characterize vibrations of a windshield of the vehicle. An artificial neural network may run on computer hardware carried on-board the vehicle. The artificial neural network may be trained to classify meteorological precipitation in an environment of the vehicle using the image data and the accelerometer data as inputs. The classifications of the artificial neural network may be used to control one or more functions of the vehicle such as windshield-wiper speed, traction-control settings, or the like.

Abstract: Example passenger validation systems and methods are described. In one implementation, a method receives, at a vehicle, a transport request indicating a passenger and a pick-up location. The vehicle drives to the pick-up location and authenticates the passenger at the pick-up location. If the passenger is successfully authenticated, the method unlocks the vehicle doors to allow access to the vehicle, determines a number of people entering the vehicle, and confirms that the number of people entering the vehicle matches a number of passengers associated with the transport request.