Aspects described herein may allow for vehicle tracking. Systems and methods described herein may allow a vehicle to automatically detect the presence of a physical marker at a parking space. An image of the physical marker may be processed to determine the location of the vehicle, which may be stored and/or output for display.

A system of estimating ambient light includes an image sensor that captures an image; a region of interest (ROI) selector that determines at least one ROI on the image; an occupancy detector that determines existence status of an object disposed on the at least one ROI; and an ambient light estimator that estimates illumination of ambient light of the at least one ROI according to luminance of the at least one ROI on the image.

Systems and methods for virtual vehicle parking assistance are disclosed herein. An example method includes determining a current vehicle position and vehicle dimensions of a vehicle, determining parking space dimensions of a parking space, receiving a desired parking position for the vehicle through an augmented reality interface, the augmented reality interface including a three-dimensional vehicle model based on the vehicle dimensions, the augmented reality interface being configured to allow a user to virtually place the three-dimensional vehicle model in the parking space to determine the desired parking position, determining a virtual parking procedure for the vehicle based on the desired parking position selected by the user and the parking space dimensions of a parking space and causing the vehicle to autonomously park based on the virtual parking procedure.

In various examples, a set of object trajectories may be determined based at least in part on sensor data representative of a field of view of a sensor. The set of object trajectories may be applied to a long short-term memory (LSTM) network to train the LSTM network. An expected object trajectory for an object in the field of view of the sensor may be computed by the LSTM network based at least in part an observed object trajectory. By comparing the observed object trajectory to the expected object trajectory, a determination may be made that the observed object trajectory is indicative of an anomaly.

Aspects of the subject technology relate to a vehicle backup warning system. A rearview image is received from a rearview camera capturing images of an area behind an own vehicle. The rearview image is determined to include a plurality of white pixels each having a luminance value equal to or above a luminance threshold. Two or more white pixels within a first distance of one another are grouped from the plurality of white pixels. The rearview image is determined to include two groups of the two or more white pixels. A distance between centers of the two groups is determined to be equal to or less than a second distance of each other. The two groups are identified as a pair of illuminated backup lights of a vehicle in the area behind the own vehicle. A warning is provided to alert that the vehicle's intention to backup.

Systems and methods are provided to generate an object detection representation of a candidate object based on sensor data representing a captured image of an environment surrounding the vehicle. A determination is made as to whether, whether the candidate object is an outlier based on the object detection representation. In response to determining the candidate object is not an outlier, the candidate object is validated as an object, a proximity distance of the object to the vehicle is determined, and the proximity distance of the object is sent as output.

An Automated Parking System (“APS”) for a motor vehicle includes a plurality of cameras for generating a vision signal, in response to the cameras capturing an image of a region surrounding the motor vehicle. The APS includes a processor for receiving the vision signal from the cameras. The APS further includes a non-transitory computer readable storage medium for storing instructions such that the processor is programmed to execute a plurality of routines. The routines include a detection module for detecting one or more landmark points in the image. The routines further include an estimate slot module for determining one or more corners of a parking slot based on the landmark points. The routines further include a maneuver module for generating an action signal, with a power steering system maneuvering the motor vehicle into the parking slot based on the corners.

Provided are an intelligent parking method and apparatus, relating to the technical field of vehicles. The method comprises: determining a target parking route from at least one pre-stored parking route; determining a target position point in the target parking route closest to a vehicle; sending a prompt message for driving the vehicle to the target position point to a driver of the vehicle when a current position point of the vehicle and the target position point satisfy a proximity matching condition; and when the vehicle drives to the target position point, controlling the vehicle to park according to the target parking route from the target position point. Thus, the driver merely needs to drive the vehicle to a vicinity of the target parking route, and the vehicle may perform intelligent parking and may complete intelligent parking at a longer distance.

A vehicle driving assist system includes a controller and a display. The controller is configured to generate a bird’s-eye view image based on information on images around a vehicle, respectively captured by cameras, and acquire a target route from a current location of the vehicle to a target stop location set by a driver. The display is configured to display the bird’s-eye view image and the target route and allow the driver to use the bird’s-eye view image to set a no entry area. The controller is configured to, when the controller determines that the vehicle enters the no entry area if the vehicle moves along the target route, correct the target route such that the vehicle does not enter the no entry area and cause the vehicle to move to the target stop location along the corrected target route and stop at the target stop location.

A process for identifying a road feature in an image includes receiving an image at a controller, identifying a region of interest within the image and converting the region of interest from red-green-blue (RGB) to a single color using the controller. A set edges is detected within the region of interest, and at least one line within the set of edges is identified using the controller. The at least one line is compared with a set of known and expected road marking features, and the set of at least one first line in the at least one line is identified as corresponding to a road feature in response to the at least the first line matching the set of known and expected road marking features.