Abstract: A method for lane and roadway detection uses a multitask DNN architecture including an encoder, a first decoder and a second decoder. The method includes the following steps: providing an input image by an optical detection device, filtering the input image by the encoder, generating a first representation of the lane and/or roadway by the encoder, processing the first representation in the first and second decoders, outputting two different representations from the first and second decoders, combining the two different representations, and outputting identified lanes, lane markings and the roadway.

Abstract: A stereo camera system for a driver assistance system includes a first camera having a first aperture angle and a second camera having a second aperture angle, wherein the first camera produces a wide-angle camera image, the second camera produces a telephoto camera image, and the two camera images have an area of overlap. The first camera is a rolling shutter camera and the second camera is a global shutter camera. The two cameras' shutters are synchronized with one another in particular manners.

Abstract: The invention relates to a method for lane detection (S1-S3) and roadway detection (1), wherein a multitask DNN architecture is used for detection and consists of at least one encoder and at least one first and one second decoder, the method comprising the following steps: providing (VS1) an input image by means of an optical detection device, filtering (VS2) the input image by means of the encoder, generating (VS3) a first representation of the lane (S1-S3) and/or roadway (1) by the encoder, forwarding (VS4) the first representation to the first and the second decoder, processing (VS5) the first representation in the first and the second decoder, outputting (VS6) two further different representations of the first and second decoder, combining (VS7) the two representations of the first and the second decoder, outputting (VS8) identified lanes (S1-S3) and lane markings and also the roadway (1).

Abstract: A method and a device for determining the position of a vehicle, said method comprising the steps: recording sensor data from the ground over which the vehicle travels; extracting ground characteristics of the ground over which the vehicle travels from the recorded sensor data or from occupancy grids which are calculated on the basis of the sensor data; determining the current position of the vehicle on the basis of the extracted ground characteristics using a characteristic map.

Abstract: A device for object recognition of an input image includes: a patch selector configured to subdivide the input image into a plurality of zones and to define a plurality of patches for the zones; a voting maps generator configured to generate a set of voting maps for each zone and for each patch, and to binarize the generated set of voting maps; a voting maps combinator configured to combine the binarized set of voting maps; and a supposition generator configured to generate and refine a supposition out of or from the combined, binarized set of voting maps.

Abstract: A control device for a vehicle, with at least one environment sensor which is designed to detect the surroundings of the vehicle, with a computing device which is designed to detect the position of the vehicle and to operate the environment sensor on the basis of corresponding location-dependent operating parameters.

Abstract: The invention relates to a camera system, in particular a stereo camera system, for a driver assistance system, comprising a first camera having a first aperture angle and a second camera having a second aperture angle, the first camera producing a wide-angle camera image and the second camera producing a telephoto camera image, the two camera images having an area of overlap. The first camera is a rolling shutter camera and the second camera is a global shutter camera, the camera system being designed in such a way that the two cameras are synchronized.

Abstract: The present invention relates to a device (100) for object recognition of an input image (A), the device (100) comprising: a patch selector (10), which is configured to subdivide the input image (A) into a plurality of zones z(m) and to define a plurality of patches pj(m) for the zones z(m); a voting maps generator (20), which is configured to generate a set of voting maps V(m) for each zone m of the plurality of zones z(m) and for each patch pj of the plurality of patches pj(m) and to binarize the generated set of voting maps V(m); a voting maps combinator (30), which is configured to combine the binarized set of voting maps V(m); and a supposition generator (40), which is configured to generate a supposition out of or from the combined, binarized set of voting maps V(m) and to perform a refinement of the supposition out of or from the combined, binarized set of voting maps V(m).

Abstract: A driver assistance system (106) of a vehicle (100) includes a laser scanner (101) with a phase-controlled laser (102), a sensor unit (104) and an evaluation unit (103). The phase-controlled laser is configured to produce a controllable laser beam by beam forming and to direct the laser beam into an environment outside of the vehicle. The sensor unit (104) is configured to detect a retroreflection caused by the laser beam. The evaluation unit (103) produces driver assistance data by evaluating the detected retroreflection.

Abstract: In order to recognize hazard areas and/or construction areas on a roadway, an environment sensor produces detected environment data regarding objects indicating the hazard areas and/or construction areas. A traffic light system is detected in the environment data, position data of the traffic light system is determined, an environment scenario is determined from the environment data and is compared with a reference model of the environment scenario. If the reference model does not indicate the presence of a traffic light system, or indicates a traffic light system having position data differing from the position data of the detected traffic light system, then it is concluded that the detected traffic light system is a traffic light system identifying a hazard and/or construction area.

Abstract: A driver assistance system for controlling a high beam, including an environment detecting device. At least one radar or lidar sensor system as well as a camera sensor system are provided for detecting the environment in front of the vehicle. A control signal for a high beam controller or warning device is generated when the high beam is active and at least one sensor system for detecting the environment simultaneously detects a potentially dazzled object.

Abstract: A sensor system detects objects in an environment ahead of a vehicle. The environment is represented by a predetermined fixed number of position points in an environment model. Initially and when no objects are detected, the position points may be distributed stochastically over the detection area of the sensor system. When objects are detected, the position points are re-distributed based on the detected objects, e.g. with a higher density of position points to represent the detected objects. Because the total number of position points is a predefined fixed number that remains constant, the processing, storage and transmission of the environment model involves a constant data volume and efficient use of memory and transmission bandwidth.

Abstract: A method for an overtaking assistant for a vehicle is provided. The vehicle is equipped with environment sensing systems for detecting objects in the own and an adjacent lane on the sides and at the rear of the vehicle. The space in front of the vehicle is preferably detected by environmental sensors as well. Autonomous cutting into an adjacent lane is only initiated if a first vehicle is detected in the adjacent lane. The first vehicle is taken as a reference for a speed of vehicles in the passing lane. It is also assumed that a second vehicle that approaches the first vehicle fast in the same lane has detected the first vehicle and will adjust its speed to the speed of the first vehicle.

Abstract: A method for adapting a collision avoidance system that avoids a collision of a vehicle with an obstacle, which collision avoidance system is designed to avoid the collision by sensing an actual distance from the obstacle and by outputting a signal on the basis of the falling below of a threshold distance by the actual distance, including: sensing a friction coefficient of an underlying surface on which the vehicle is supported in such a way that the vehicle can be driven, and setting the threshold distance on the basis of the sensed friction coefficient.

Abstract: A method and a device for analyzing trafficability use a computer to perform the following steps: receiving image data representing an image of surroundings in front of a vehicle, analyzing the image data to identify different zones in the image of the surroundings, and analyzing the identified different zones in terms of trafficability thereof for the vehicle.

Abstract: A method and a device for determining the position of a vehicle, said method comprising the steps: recording sensor data from the ground over which the vehicle travels; extracting ground characteristics of the ground over which the vehicle travels from the recorded sensor data or from occupancy grids which are calculated on the basis of the sensor data; determining the current position of the vehicle on the basis of the extracted ground characteristics using a characteristic map.

Abstract: A method and a device are provided for detecting the condition of a pavement or roadway travel surface on which a vehicle is traveling. A 3D camera acquires 3D camera image data including at least one image of surroundings including the roadway travel surface extending in front of the vehicle in the direction of motion thereof. Transverse height profiles of the roadway travel surface that respectively extend along transverse lines extending transversely to the vehicle's direction of motion are determined from the 3D camera image data. The condition of the roadway travel surface is detected from the determined transverse height profiles.

Abstract: A control device for a vehicle, with at least one environment sensor which is designed to detect the surroundings of the vehicle, with a computing device which is designed to detect the position of the vehicle and to operate the environment sensor on the basis of corresponding location-dependent operating parameters.

Abstract: A method for learning traffic events, the traffic events being transmitted to a data network using vehicle-to-X communication. The traffic events include position data and time data assigned to the traffic events, and the traffic events are stored electronically in the data network. The method is characterized in that an individual storage duration is determined for each traffic event, and the traffic event is deleted from the data network after the storage duration expires. The invention further relates to a corresponding system and to the use thereof.

Abstract: The present disclosure relates to a device for measuring distance using a camera. The camera is movably arranged on a camera holder. A controller is designed to control a movement of the camera, in particular in a stationary state of the device, in such a manner that the camera records at least two images in at least two positions. A computing device is designed to calculate and output the distance of the device from objects visible on the images based on the at least two images. Further, the present disclosure discloses a vehicle and a method.