A method for vehicle parking detection, a system for vehicle parking detection, an electronic device and a storage medium are disclosed. The method includes: obtaining a first lateral distance between a vehicle and a reference object in a site by a first distance sensor; obtaining a second lateral distance between the vehicle and the reference object by a second distance sensor; collecting a first scene image by a first camera, and obtaining a first longitudinal distance based on the first scene image, the first longitudinal distance being a distance between a first mark line on the vehicle and a first parking line in the site; and determining whether the vehicle is parked at a target location in the site based on the first lateral distance, the second lateral distance and the first longitudinal distance.

System, methods, and other embodiments described herein relate to lane keeping in a vehicle. In one embodiment, a method includes determining lane boundaries according to at least the sensor data and a map. The method includes defining a reference system over a lane defined by the lane boundaries. The method includes evaluating vehicle boundary points within the reference system as a cost in optimizing a trajectory of the vehicle and using an R-function that defines geometric relationships between the vehicle boundary points and the reference system. The method includes providing an indicator about the trajectory to control the vehicle.

An information display apparatus may include a processor configured to display a display object in augmented reality; and a storage configured to store data and algorithms driven by the processor, wherein the processor determines a position of the display object by use of at least one of a total number of lanes or a number of lanes in a road in a driving direction of a host vehicle, possible traveling direction information for each lane, and driving direction information related to the host vehicle, and the information display apparatus is disposed within a vehicle or outside the vehicle, and when disposed outside the vehicle, is configured to transmit display information related to the display object to the vehicle or a mobile device.

A system and method for determining car to lane distance is provided. In one aspect, the system includes a camera configured to generate an image, a processor, and a computer-readable memory. The processor is configured to receive the image from the camera, generate a wheel segmentation map representative of one or more wheels detected in the image, and generate a lane segmentation map representative of one or more lanes detected in the image. For at least one of the wheels in the wheel segmentation map, the processor is also configured to determine a distance between the wheel and at least one nearby lane in the lane segmentation map. The processor is further configured to determine a distance between a vehicle in the image and the lane based on the distance between the wheel and the lane.

To make error correction in a position estimate of a vehicle, visual lane markings on the road can be matched with lane boundaries for the road within 3-D map data. Embodiments include obtaining a “stripe” indicative of an observed lane marking captured in a from a camera image, obtaining map data for the road on which the vehicle is located, determining the plane of the road from coordinates of lane boundaries within the map data, projecting the stripe onto the plane, and comparing the projected stripe with lane boundaries within the map data and associating the visual lane markings with the closest lane boundary. Differences between the projected stripe and the associated lane boundary can then be used for error correction in the position estimate of the vehicle.

In some implementations, a method is provided. The method includes obtaining an image depicting an environment where an autonomous driving vehicle (ADV) may be located. The image comprises a plurality of line indicators. The plurality of line indicators represent one or more lanes in the environment. The image is part of training data for a neural network. The method also includes determining a plurality of line segments based on the plurality of line indicators. The method further includes determining a vanishing point within the image based on the plurality of line segments. The method further includes updating one or more of the image or metadata associated with the image to indicate a location of the vanishing point within the image.

This application provides a positioning solution, wherein the solution includes: determining first feature information and semantic category information of a first road-related element in an image, wherein the image is taken by a mobile device in a moving process; determining second feature information of a second road-related element whose semantic category information is identical to the semantic category information in a high-definition map; and positioning the mobile device based on a matching result of the first feature information and the second feature information.

System, methods, and other embodiments described herein relate to improving a representation of objects in a surrounding environment. In one embodiment, a method includes, in response to receiving sensor data depicting the surrounding environment including a corridor that defines a left boundary and a right boundary, identifying at least one object from the sensor data. The method includes transforming segmented data from the sensor data that represents the object into a bounding box by defining the bounding box according to six points relative to the corridor. The method includes providing the six points of the bounding box as a reduced representation of the object.

A road-surface state determination apparatus for a vehicle is provided. The road-surface state determination apparatus includes an acquiring unit and a control unit. The acquiring unit acquires, as a first detection signal, information on a changed pixel of which a luminance value changes based on an absolute displacement of a road-surface state or a relative displacement of the road-surface state relative to a moving vehicle. The control unit determines a type of the road-surface state using the first detection signal.

Systems and methods are provided for navigating based on sensed brake light patterns. In one implementation, a navigation system for a host vehicle may include at least one processing device. The at least one processing device may be programmed to receive, from a camera, a plurality of images representative of an environment ahead of the host vehicle; analyze the plurality of images to identify at least one target vehicle in the environment ahead of the host vehicle; identify, based on analysis of the plurality of images, at least one brake light associated with the target vehicle and at least one characteristic associated with changes in an illumination state of the at least one brake light; and cause a navigational change for the host vehicle based on the identified at least one characteristic associated with the changes in the illumination state of the at least one brake light.