An apparatus for providing an around view comprises: first and second cameras for acquiring first and second image information; and a processor. The processor can generate an around view image including a first area including a subject overlapping area and a second area excluding the subject overlapping area, on the basis of first and second images. The subject overlapping area is disposed between first and second boundary lines in the first and second images. The first boundary line is located in the first area, and the second boundary line adjoins the second area. If it is predicted that a first object will pass through the second boundary line due to the first object approaching within a predetermined distance thereto, the processor can generate an around view image in which the second area is changed so that the second area includes the subject overlapping area.

In one embodiment, a method includes receiving autonomous-vehicle sensor data from a sensor array of an autonomous vehicle. The autonomous-vehicle sensor data indicates an object in an external environment of the autonomous vehicle. The method also includes accessing secondary data associated with the object from one or more secondary-data sources that are independent of the sensor array of the autonomous vehicle. The method also includes determining, based on the autonomous-vehicle sensor data and the secondary data, an object graphic to visually represent the object. The method also includes providing for display a visual representation of the external environment of the autonomous vehicle that includes the determined object graphic to visually represent the object.

Systems and methods are provided for navigating a host vehicle. A processing device may be programmed to receive an image representative of an environment of the host vehicle; determine a planned navigational action for the host vehicle; analyze the image to identify a target vehicle travelling toward the host vehicle; determine a next-state distance between the host vehicle and the target vehicle that would result if the planned navigational action was taken; determine a stopping distance for the host vehicle based on a braking profile, a maximum acceleration capability, and a current speed of the host vehicle; determine a stopping distance for the target vehicle based on a braking profile and a current speed of the target vehicle; and implement the planned navigational action if the determined next-state distance is greater than a sum of the stopping distances for the host vehicle and the target vehicle.

A method for validation of an obstacle candidate identified within a sequence of image frames comprises the following steps: A. for a current image frame of the sequence of image frames, determining within the current image frame a region of interest representing the obstacle candidate, dividing the region of interest into sub-regions, and, for each sub-region, determining a Time-To-Contact (TTC) based on at least the current image frame and a preceding or succeeding image frame of the sequence of image frames; B. determining one or more classification features based on the TTCs of the sub-regions determined for the current image frame; and C. classifying the obstacle candidate based on the determined one or more classification features.

A system for operating an automated vehicle in a crowd of pedestrians includes an object-detector, optionally, a signal detector, and a controller. The object-detector detects pedestrians proximate to a host-vehicle. The signal-detector detects a signal-state displayed by a traffic-signal that displays a stop-state that indicates when the host-vehicle should stop so the pedestrians can cross in front of the host-vehicle, and displays a go-state that indicates when the pedestrians should stop passing in front of the host-vehicle so that the host-vehicle can go forward. The controller is in control of movement of the host-vehicle and in communication with the object-detector and the signal-detector. The controller operates the host-vehicle to stop the host-vehicle when the stop-state is displayed, and operates the host-vehicle to creep-forward after a wait-interval after the traffic-signal changes to the go-state when the pedestrians fail to stop passing in front of the host-vehicle.

An automobile head up display system and an obstacle prompt method thereof are provided. The method includes: acquiring a road condition video image, identifying obstacles from the acquired image after performing an enhancement processing on the acquired image; projecting and displaying a prompt information at corresponding positions of a front windshield of the automobile according to positions of the identified obstacles in the road condition video image.

A vehicle(100) may include one or more image sensors(110) configured to provide sensor image data (112d) representing a sensor image of a vicinity of the vehicle(100), and one or more processors(120) configured to determine one or more obstacles (132) from the sensor image data(112d), to determine a distance from ground for each of the one or more obstacles (132) based its corresponding image object(114), and to trigger a safety operation when the distance from ground is equal to or less than a safety height associated with the vehicle(100). A method for avoiding a collision of a vehicle with one or more obstacles.

A method, an apparatus, a device, and a medium for calibrating a posture of a moving obstacle are provided. The method includes: obtaining a 3D map, the 3D map including first static obstacles; selecting a target frame of data, the target frame of data including second static obstacles and one or more moving obstacles; determining posture information of each of the one or more moving obstacles in a coordinate system of the 3D map; registering the target frame of data with the 3D map; determining posture offset information of the target frame of data in the coordinate system according to a registration result; calibrating the posture information of each of the one or more moving obstacles according to the posture offset information; and adding each of the one or more moving obstacles after the calibrating into the 3D map.

An apparatus and method automatically detects and positions structure faces. After receiving data points describing a geographical area, neighborhoods are defined based on the data points and classified as linear, planar, or volumetric. Neighborhoods are merged into at least one cluster based on local surface normals. At least one bounding frame is fit to the at least one cluster and modified based on a field of interest.

The purpose of the present invention is to provide an onboard environment recognition device exhibiting high accuracy of measurement in a wider range of view fields. The present invention pertains to an onboard environment recognition device (1) that utilizes two cameras (100, 110) for sensing, wherein the onboard environment recognition device (1) is characterized in that: two camera view fields include a stereo-vision area and a monocular-vision area; and the device laterally searches for parallax images that are output results of the stereo-vision area, estimates a road surface distance in the stereo-vision area, and measures the distance of the monocular-vision area by using the estimated road surface distance after extending the same to the monocular-vision area in the lateral direction.