Control determines whether or not two objects represent the same object, in which one object is detected at a first position in front of a vehicle by an electromagnetic wave sensor and the other object is detected at a second position in front of the vehicle by image sensor. The control further determines whether or not the other object is partially excluded from an image acquired by the image sensor, in which a part of the object may have been outside the imaging region of the image sensor. The control changes a determination condition used for determining whether or not the objects represent the same object, such that the object whose part is excluded from the acquired image is more easily determined as the same object, compared with an object determined that such a part is not excluded from the acquired image.

An object detection method includes obtaining a first video stream having video images with object detection data of an area, identifying an object in the area by identifying one or more first object detection data of the object in the first video stream corresponding to validated object detection data, determining a position of the object in the area, obtaining a second video stream having video images with object detection data of the area, identifying second object detection data of the second video stream at the position of the object and determining whether the second object detection data is un-validated object detection data, and updating the validated object detection data of the object detection system if it is determined that the second object detection data of the object is un-validated object detection data.

A method for determining a quality of a surface in the surroundings of a transportation vehicle, wherein three-dimensional surface coordinates of the surface are generated using a sensor assembly. In the method, an approximation of the course of the curvature of the surface in at least one direction is obtained based on the surface coordinates and the surface coordinates are classified to characterize the quality of the surface using the course of the curvature and/or vertical distances of the approximation of the course of the curvature from the three-dimensional surface coordinates. A device for carrying out the method.

The disclosure provides a method for operating an autonomous vehicle. To operate the autonomous vehicle, a plurality of lane segments that are in an environment of the autonomous vehicle is determined and a first object and a second object in the environment are detected. A first position for the first object is determined in relation to the plurality of lane segments, and particular lane segments that are occluded by the first object are determined using the first position. According to the occluded lane segments, a reaction time is determined for the second object and a driving instruction for the autonomous vehicle is determined according to the reaction time. The autonomous vehicle is then operated based on the driving instruction.

Embodiments of the present disclosure disclose a method and an apparatus for detecting an obstacle, an electronic device, a vehicle and a storage medium. The method includes: obtaining a depth map around a vehicle; performing a terrain fitting based on the depth map to determine a terrain equation; determining a set of candidate obstacle points based on the terrain equation and the depth map; clustering candidate obstacle points in the set of candidate obstacle points to obtain at least one independent obstacle; and identifying and filtering a falsely detected obstacle from the at least one independent obstacle to obtain a depth-map-based obstacle detection result.

An image processing device includes: a solid object extraction unit that divides each of a plurality of captured images into a foreground image part occupied by an existent object and a background image part; a background complementing unit that complements each background image part; a background image synthesis unit that generates a background bird's eye synthetic image by performing bird's eye transformation and combining together the background image parts after undergoing the bird's eye transformation; a solid object recognition unit that acquires posture information on the existent object; a solid object projection unit that acquires a three-dimensional virtual object by using the posture information; a three-dimensional space superimposition unit that generates a three-dimensional space image by superimposing the three-dimensional, virtual object on the background bird's eye synthetic image; and a display image output unit that outputs a bird's eye synthetic image generated based on the three-dimensional space image.

An operating assistance method for a working device or for a vehicle. Object boxes for an object in a field of view of the working device are obtained at consecutive times. From object boxes of a given object, for images recorded in succession or direct succession, an instantaneous change of scale of an object box for the specific object, and an instantaneous lateral change of position of the object box for the specific object, are determined. An object box predicted in the future is determined from the current change of scale, and from the instantaneous lateral change in position for an object box for a specific object. The position of the predicted object box and/or the ratio of a lateral extension of the predicted object box to a lateral extension of a covered field of view and/or of the recorded images are determined and evaluated.

A first pixel group disposed in a first direction is read in the first direction. A second pixel group adjacent to the first pixel group is read in a second direction, which is opposite to the first direction.

An image processing apparatus includes an input interface to acquire an image, and first to fourth controllers. The first controller performs image processing on the image. The second controller performs correction on an optical distortion in the image. The third controller performs recognition on the image. The fourth controller superimposes a result of the recognition onto the image and outputs a resulting image. The first controller can perform first and second image processing. The second controller can perform first and second correction processing. The third controller receives an input of the image, and outputs information indicating a location of a recognized object. The fourth controller receives an input of the image, and superimposes a drawing indicating the location of the recognized object onto a corresponding location in the image.

Provided are a system, apparatus, and method for vehicle control and more particularly. The apparatus includes a first spatial information generator configured to generate first spatial information at a vicinity of a host vehicle, based on at least one of image data or sensing data, a vehicle specification receiver configured to receive first vehicle information, which is vehicle information of at least one of external vehicles existing the vicinity of the host vehicle and a second spatial information generator configured to generate second spatial information of the vicinity of the host vehicle by modifying the first spatial information based on the first vehicle information.