A vehicle control system for moving a vehicle to a target location is disclosed. According to examples of the disclosure, a camera captures one or more images of a known object corresponding to the target location. An on-board computer having stored thereon information about the known object can process the one or more images to determine vehicle location with respect to the known object. The system can use the vehicle's determined location and a feedback controller to move the vehicle to the target location.

A pose determining method, which may be applied to the field of photographing and image processing, includes: obtaining a target image, where the target image includes a target parking space mark and a target parking space line, and a target parking space corresponding to the target parking space mark includes the target parking space line; and determining pose information based on the target parking space mark and the target parking space line. The pose information indicates a corresponding pose of a terminal during photographing of the target image. According to the pose determining method, the pose information may be determined based on the target parking space mark and the target parking space line, to implement positioning.

Stitching of multiple images into a composite representation can be performed using a set of stitching parameters determined based, at least in part, upon a subjective stitching quality assessment value. A stitched image can be compared against its constituent images to obtain one or more objective quality metrics. These objective quality metrics can be fed, as input, to a trained classifier, which can infer a subjective quality assessment metric for the stitched (or otherwise composited) image. This subjective quality assessment metric can be used to adjust one or more compositing parameter values in order to provide at least a minimum subjective quality assessment value for composited images.

A system includes a processor and a memory storing instructions that, when executed by the processor cause the system to generate a machine learning model; generate an artificial neural network; analyze an image of a parking area using a spot detection machine learning model; analyze the image of the parking area using a vehicle detection machine learning model; and classify a parking space as available when an area of intersection does not exceed a predetermined value. A method includes analyzing an image of a parking area using a first machine learning model; analyzing the image of the parking area using second machine learning model; and classifying a parking space as available when an area of intersection does not exceed a predetermined value. A method includes generating a spot detection machine learning model; and generating, by analyzing a plurality of labeled images, an artificial neural network.

A control device for automated valet parking lot includes: a travel route determining unit configured to determine a travel route to a parking space; a travel route transmission unit configured to transmit the travel route to a vehicle; a position acquiring unit configured to acquire, from the vehicle, a position of the vehicle that is estimated by the vehicle while traveling; and a positional accuracy calculation unit configured to calculate a dynamic estimation accuracy, which is an accuracy of the position of the vehicle acquired by the position acquiring unit from the vehicle while the vehicle is travelling, prior to performing automated driving of the vehicle in accordance with the travel route.

A method for automated parking, a device, and a storage medium, which relate to a field of automated parking. The method for automated parking includes: determining, based on a historical location of a vehicle over a first time period, a frequented region associated with one or more candidate parking routes for the vehicle; acquiring the one or more candidate parking routes for the vehicle based on one or more historical parking routes of the vehicle in the frequented region, where the one or more historical parking routes include a driving-in route and/or a driving-out route; and providing the vehicle with the acquired one or more candidate parking routes in response to determining that the vehicle is in the frequented region, for the vehicle to drive in or drive out.

Provided is a display control apparatus that generates a display overhead image including overhead images of each of a vacant parking space and a vehicle and outputs the display overhead image to a display apparatus. The display overhead image includes at least one of an overhead image of the vacant parking space outside of a current viewing angle of a vehicle-mounted camera and an overhead image of the vacant parking space hidden behind a static object as seen from a current position of the vehicle.

A system, comprising a computer having a processor and a memory storing instructions executable by the processor to identify a height of a curb that is at least one of within or bordering a parking area having a specified length and width. The instructions include instructions to identify a location of the curb. The instructions include instructions to determine a parking position within the parking area based on the height of the curb and the location of the curb. The instructions include instructions to park a vehicle at the parking position within the parking area.

Methods, systems, and apparatus for a detection system for a vehicle. The detection system includes at least one of a camera or a sensor. The camera is configured to capture image data of a surrounding environment. The sensor is configured to detect sensor data. The detection system includes an electronic control unit. The electronic control unit is coupled to the camera and is configured to determine that there is an available parking spot or a person is positioned on a side of a road based on the image data or the sensor data. The electronic control unit is configured to provide a location of the available parking spot or the person to another device or to the vehicle.

The present disclosure provides a method and apparatus for an automatic parking system. The method includes: obtaining a parking-line segmentation image through a segmentation neural network; preprocessing the parking-line segmentation image to obtain at least one parking-line skeleton image; and calculating straight-line equations and straight-line endpoints for parking lines in the parking-line segmentation image based on the at least.