Abstract: Methods and systems for displaying image data in a vehicle are disclosed herein. A method for displaying image data include providing initial and final projection surfaces; receiving a video stream and is buffered in a buffer storage, which is updated at a frame rate. The method includes reading out image data at a readout rate from the buffer at an initial readout instance, intermediate readout instances and a final readout instance. The method includes determining respective sets of initial and final sampling points on the projection surfaces. For each of the intermediate readout instances, the method includes determining intermediate sampling points, which interpolate between the final sampling points and the respective initial sampling points, and an intermediate projection surface containing the intermediate sampling points. The method includes projecting the read out image data to the respective intermediate projection surface and a corresponding image is displayed on a display device.

Abstract: A camera for a motor vehicle is disclosed. The camera includes a housing, wherein a receiving space, in which a lens module of the camera and a circuit board of the camera are arranged, is bounded by the housing. The camera has a longitudinal axis, wherein the circuit board and the lens module are arranged axially spaced from each other in the direction of this longitudinal axis such that a clearance is formed between the circuit board and the lens module. An elastic seal is arranged between the circuit board and the lens module such that the clearance is sealed from the remaining volume space in the housing by the seal.

Abstract: For computing height information of a curb, line segments approximating the curb in a ground plane are determined, a perpendicular bisector of a first line segment is computed, and a second segment are determined, which intersects the perpendicular bisector. A first plane including the first segment and a second plane including the second segment are determined. A midpoint of the first segment is projected to the second plane and an intersection point of the second segment is projected to the first plane. Depending on respective resulting heights, the first and the second segment are classified as upper and lower, respectively. An upper point of the upper segment is projected to a further plane, which is perpendicular to the ground plane and includes the lower segment, and a height of the projected upper point above the ground plane is determined.

Abstract: A MEMS device is provided with an actuator stator providing an electrical connection point. The MEMS device includes an electrical distribution substrate, and an actuator stator positioned above it. The actuator stator has a floor and an outer frame extending up from the floor. The MEMS device includes a stator pad disposed on the outer frame and above the electrical distribution substrate. The MEMS device also includes an actuator rotor suspended above the floor, within the outer frame, with a sensor mounted thereon. A wire bond interconnect electrically couples the sensor to the stator pad. In some embodiments, the outer frame includes a via extending therethrough which electrically connects the stator pad with the electrical distribution substrate, enabling an electrical connection between the sensor and the electrical distribution substrate. In some embodiments, a second wire bond interconnect electrically connects the stator pad and the substrate.

Abstract: A method for automatic visual perception includes generating first feature maps from a camera image by a first encoder module of a neural network and the first feature maps are transformed into a top view perspective, emitting an ultrasonic pulse into the environment and generating an ultrasonic sensor signal depending on reflected portions of the emitted ultrasonic pulse. The method includes generating a spatial ultrasonic map depending on the ultrasonic sensor signal and generating second feature maps from the ultrasonic map by a second encoder module of the neural network. The method includes fusing the transformed first feature maps and the second feature maps and carrying out a visual perception task by a decoder module of the neural network depending on the fused feature maps.

Abstract: A MEMS device includes an electrical distribution substrate and a spacer ring extending upward therefrom. An actuator stator is positioned above the electrical distribution substrate and within the spacer ring. An outer frame extends from a floor of the actuator stator. An actuator rotor is suspended above the floor. A sensor is supported by the actuator rotor. A conductive stack is positioned above the spacer ring. A wire electrically connects the sensor to the conductive stack. A plurality of vias extending through the spacer ring and to the electrical distribution substrate, thereby allowing electrical communication between the sensor and the electrical distribution substrate while enabling vertical displacement of the sensor and actuator rotor.

Abstract: A method includes obtaining image frames from each camera disposed along a vehicle, where each image frame corresponds to a same timestamp. The method further includes constructing a first birds-eye view (BEV) image from each image frame with a first BEV module and constructing a second BEV image from each image frame by Inverse Perspective Mapping (IPM) with a second BEV module. The first BEV module extracts features of an external environment of the vehicle from each image frame, transforms the features to a three-dimensional space, and projects the three-dimensional space onto an overhead two-dimensional plane. Subsequently, a merging module merges the first and second BEV images to produce a hybrid BEV image. Features of an external environment of the vehicle within the hybrid BEV image are detected by a deep learning neural network and the hybrid BEV image is displayed to a user in the vehicle.

Abstract: In some implementations, the device may include receiving, via an image sensor associated with a vehicle, an image of a parking area. In addition, the device may include determining that the image of the parking area includes an available parking spot; analyzing the image of the parking area to locate a number associated with the available parking spot; determining that the vehicle is entering the available parking spot; creating, in response to the vehicle entering the available parking spot, a generated image that includes the number associated with the available parking spot based on the image of the parking area; and displaying the generated image on a vehicle display in response to the vehicle occupying the available parking spot.

Abstract: A composite top view of an area surrounding a vehicle is generated utilizing image harmonization and proximity sensor data. Images from various vehicle cameras are received, wherein at least two of the cameras can see the same portion of the environment in an overlapping region. The images are segmented into segments. The overlapping regions include some of the segments of one image and some of the segments of another region to define overlapping segments. Sensor data is received from a plurality of proximity sensors, wherein the sensor data indicates a location of an object outside of the vehicle. The color and/or brightness of the images are harmonized based at least in part on the sensor data. In particular embodiments, weights are placed on the color and/or brightness of the overlapping segments associated with the location of the object. Or these overlapping segments can be removed from the harmonization.

Abstract: In the field of micro-electromechanical systems (MEMS) for autofocus camera systems, a MEMS device comprises a fixed part, a movable platform with an image sensor, and temperature sensors on both the platform and fixed part. A processor calculates the temperature difference to determine the platform's displacement. This method eliminates the need for additional capacitive or piezoelectric components, reducing complexity and cost. The described technology is particularly useful in consumer electronics, such as smartphone and automotive cameras, where precise focus control may be vital.

Abstract: A method, for detecting an artefact in a stitched image, comprises: acquiring component images of an environment from respective vehicle mounted cameras with overlapping fields of view; forming (410) a stitched image from the component images; processing (420) at least a portion of the stitched image corresponding to the overlapping field of view with a classifier to provide a list of detected objects from the environment at respective locations in the stitched image; determining (430) whether any detected object in the list of detected objects is a duplicate of another object in the list of detected objects; and reporting any objects that are determined to be duplicates.

Abstract: A system for creating online vectorized maps for autonomous vehicles includes an image sensor and an electronic control unit (ECU). The image sensor captures a series of image frames. The ECU includes a memory, a central processing unit (CPU), and a transceiver. The memory stores a semantic segmentation deep learning model and a vectorization post-processing module as computer readable code. The CPU executes the semantic segmentation deep learning model and the vectorization post-processing module to output a vectorized map of an external environment of a vehicle. The transceiver uploads the vectorized map to a server such that the vectorized map can be accessed by a second vehicle that uses the vectorized map to traverse the external environment.

Abstract: A method for focal adjustment of an automotive camera is disclosed. The method includes providing a target focal setting for the camera for predefined regions of interest, determining a first and second focal setting for each subset of regions of interest depending on the respective target focal settings of the regions, capturing a first and second image during the first frame period respectively. The first and second focal settings are used during at least part of the first and second frame periods respectively. Between the capturing of the first and second images, the first focal setting is changed to the second focal setting.

Abstract: An electronic control system for a vehicle includes a first and a second electronic control unit (ECU) including a first and a second circuit carrier, respectively, as well as a first and a second cooling channel, respectively. The cooling channels each include respective coolant inlets and coolant outlets. A hydraulic manifold of the electronic control system includes a main inlet, a main outlet, a first and a second ECU outlet as well as a first and a second ECU inlet, to distribute the coolant from the main inlet to the first and the second ECU and from the first and the second ECU to the main outlet.

Abstract: A circuit board arrangement includes at least one housing, in which a plurality of circuit boards is arranged, and at least one cooling device, through which a cooling fluid can be passed and which is formed for dissipating heat from at least one of the circuit boards. The circuit board is thermally coupled to the cooling device by a heat transfer element. The respective circuit board is pivotable from a mounting position, in which the heat transfer element abuts both on the cooling device and on the circuit board, around a pivot axis into an intermediate position. In the intermediate position, an edge area of the circuit board far from the pivot axis is further spaced from the cooling device than in the mounting position. The housing includes at least one guide element. The respective circuit board is displaceable along the at least one guide element into the intermediate position.

Abstract: For training a perception algorithm to detect an emergency vehicle, respective audio datasets are received from two microphones and respective spectrograms are generated. At least one interaural difference map is generated based on the spectrograms, audio source localization data is generated, which specifies a number of audio sources in respective grid cells of a spatial grid, by applying a CRNN to first input data containing the spectrograms and the least one interaural difference map. An image is received from a camera and output data comprising a bounding box for the emergency vehicle is predicted by applying at least one further ANN to second input data containing the image and the spectrograms. Network parameters are adapted depending on the output data and the audio source localization data.

Abstract: A vehicle light system includes a plurality of light banks connected to a vehicle and configured to project light that radiates away from the vehicle. Each light bank includes a plurality of light sources. An image sensor, such as a camera, is connected to the vehicle and is configured to generate image data corresponding to a scene about the vehicle. A controller is connected to the light banks and the image sensor. The controller is configured to receive the image data, and execute an object detection machine learning model based on the image data to detect an object, determine a location of the object, and classify the detected object. The controller is configured to then select and dim one or more of the plurality of light sources based on the output of the object detection machine learning model. The dimming can vary based on the object class.

Abstract: The invention relates to an electrical ventilator (7) for a temperature control device (16) of an electronic computing device (3), with a housing (10), in which an electrical ventilation device (17) of the electrical ventilator (7) is arranged, and with an electrical contact device (14), which is formed for contacting with a further electrical contact device (15) of the electronic computing device (3), wherein the contact device (14) is formed for transferring at least electrical energy from the electronic computing device (3) to the electrical ventilation device (17), wherein the housing (10) comprises a shaft (18), which is formed for plunging into a recess (19) corresponding thereto on a further housing (9) of the electronic computing device (3) in certain areas, wherein the contact device (14) is fixed in the shaft (18) and is formed for wirelessly and directly contacting with the further contact device (15).

Abstract: A method for providing a yaw angle (105a) between a first vehicle (110) coupled to a second vehicle (100), comprises: receiving an image of the first vehicle from a camera (101) mounted on the second vehicle; performing (210) a polar transformation on the image to form a polar image (400) in a polar space having an origin corresponding to a location of a pivot point (303) of the coupling (302) to the second vehicle in the received image coordinate space; estimating (230) an optical coupling angle by analysing the content of the polar image; receiving a signal from an odometer (102) mounted on the first or second vehicle; estimating a kinematic coupling angle from the signal and a kinematic model of the first vehicle and the coupled second vehicle; and combining the estimated optical coupling angle and the estimated kinematic coupling angle to provide the coupling angle.

Abstract: A system for creating online vectorized maps for autonomous vehicles includes an image sensor and an electronic control unit (ECU). The image sensor captures a series of image frames. The ECU includes a memory, a central processing unit (CPU), and a transceiver. The memory stores a semantic segmentation deep learning model and a vectorization post-processing module as computer readable code. The CPU executes the semantic segmentation deep learning model and the vectorization post-processing module to output a vectorized map of an external environment of a vehicle. The transceiver uploads the vectorized map to a server such that the vectorized map can be accessed by a second vehicle that uses the vectorized map to traverse the external environment.