A method for determining at least one anchor for an anchor-based lane line recognition and/or roadway marking recognition in a digital image representation on the basis of sensor data that are obtained from at least one surroundings sensor of a system. The method includes at least the following steps: a) receiving a digital image representation, b) setting at least one row or one column of possible anchors in at least one area of the digital image representation, the row or column of possible anchors being situated at a distance from at least the upper and lower or left and right edge of the area of the digital image representation.

A method of detecting at least one traffic lane and/or a roadway marking in at least one digital image representation based on sensor data obtained from at least one environmental sensor of a system. The method includes: a) obtaining a plurality of digital image representations each containing a plurality of features representing the respective image content, b) applying a bird's eye view transformation to the obtained digital image representations, wherein each of the digital image representations is transformed separately so as to create transformed digital image representations, c) performing a consolidation of the transformed digital image representations to obtain a consolidated digital image representation.

A vehicle includes: camera monitoring apparatus including a side-view camera having a field of view facing a rear lateral side of the vehicle and a side-view display configured to display a side-view image captured by the side-view camera; and a driver assistance system including a corner radar having a field of view facing a side of the vehicle, and configured to process radar data of the corner radar. The driver assistance system is configured to provide the camera monitoring apparatus with a virtual side-view image based on processing of the radar data of the corner radar when a failure of the side-view camera is detected. The camera monitoring apparatus is configured to display the virtual side-view image of the driver assistance system on the side-view display based on the failure of the side-view camera.

Provided is an infrastructure and a vehicle for communicating with the same. The infrastructure recognizes a first area and a second area, and when a proportion of the second area of the image information is greater than or equal to a reference proportion, controls first and second adjusters to change a photographing area of a camera. The vehicle recognizes a hidden area, when a proportion of the hidden area is greater than or equal to a reference proportion, transmits an adjustment command of the first camera to the infrastructure, and when the proportion of the hidden area is less than the reference proportion. The vehicle matches an image of the hidden area to second image information of the second camera to generate a top view image.

A method used for deriving a control variable for lateral guidance of a motor vehicle by means of images of at least one camera of the motor vehicle, wherein the at least one camera captures images of a roadway. A more precise and/or resource-saving derivation of the control variable, and thus lateral guidance, of the motor vehicle is achieved by projecting a traffic lane to be followed as well as a travel trajectory of the motor vehicle onto the images, and by a control variable for lateral guidance of the motor vehicle being derived by comparing the traffic lane projected onto the images with the travel trajectory projected onto the images. A motor vehicle in which the method is performed is also described.

The wrong-way driving determination method includes acquiring a backward image of the vehicle, recognizing a target included in the backward image, and determining the wrong-way driving of the vehicle based on the recognition information of the target. Here, determining the wrong-way driving includes determining whether or not the recognition information of the target includes the recognition information of the guide display surface of the traffic sign. When it is determined that the recognition information of the guide display surface is included in the recognition information of the target, it is determined that the vehicle is traveling in the wrong direction.

An information processing apparatus includes: a point group data acquisition unit configured to acquire, based on information from a sensor configured to detect an object existing in surroundings of a vehicle, point group data related to a plurality of points representing the object; a movement amount estimation unit configured to estimate a movement amount of the vehicle; a storage unit configured to store, as a point group map recorded in association with position information including a latitude and a longitude, relative positions of the plurality of points relative to a first reference position that is a place on a travel path of the vehicle; and a position estimation unit configured to estimate a position of the vehicle based on the point group map, the point group data, and the movement amount.

A motion detecting section detects a change in relative position relation between a subject and an image capturing section performing a rolling shutter operation. A thinning-out setting section sets a thinning-out amount of a line thinning-out operation of the image capturing section according to the detection result obtained by the motion detecting section. A recognition processing section performs subject recognition in an image obtained by the image capturing section, by using a recognizer corresponding to the thinning-out amount set by the thinning-out setting section. The change in relative position relation is detected based on motion of a moving body on which the image capturing section is mounted, an image capturing scene, an image obtained by the image capturing section, and the like. Line thinning-out is performed during the rolling shutter operation, and the thinning-out amount is set according to the detection result obtained by the motion detecting section.

An image detection method determines a target object. A plurality of original images of a scene in front of a vehicle are obtained. An object in one original image is detected, and a degree of similarity between the object in the original image and the target object in a preset image is calculated. If the degree of similarity is greater than a preset similarity threshold, it is determined that the original image is a target image and the object is the target object. A position of the target object relative to the vehicle is determined and output. The method can recognize objects of interest in front of a driver.

An automatic steering control device includes a forward recognition device, a traveling state detector, a lateral positional deviation calculator, a steering angle controller. The lateral positional deviation calculator calculates a first lateral positional deviation that is the lateral positional deviation ahead of the vehicle by a first distance, and a second lateral positional deviation that is the lateral positional deviation ahead of the vehicle by a second distance larger than the first distance. The steering angle controller performs first control on the steering angle so that an absolute value of the first lateral positional deviation decreases, and second control on the steering angle based on the second lateral positional deviation so that a difference between a change amount of the steering angle in the first control and a change amount of an actual steered angle that is a steered angle of wheels of the vehicle decreases.