Abstract: A mono camera based depth perception system for a vehicle includes a mono camera system configured to capture image data of an environment external to the vehicle, the environment including a set of markings that are recognizable by the mono camera system and a control system configured to determine depth from the mono camera system or the vehicle to the set of markings based on the captured image data and known parameters of the set of markings, localize a position of the vehicle within the environment based on the determined depth, and control operation of the vehicle based on its localized position within the environment.

Abstract: An infrared (IR) assisted object segmentation and range perception system and method for a vehicle each utilize a camera system configured to capture image data of an environment external to the vehicle, the image data including unfiltered IR data, and a control system configured to generate an environmental model for the environment external to the vehicle by (i) performing object segmentation of one or more objects in the captured image data based on the unfiltered IR data and (ii) based on the object segmentation, perform range perception of the one or more objects, and utilize the generated environmental model during operation of the vehicle.

Abstract: A distributed mesh network for a vehicle includes a first high performance computing (HPC) electronic control unit (ECU) configured to execute a load prioritization and balancing technique and a second HPC ECU configured to execute the load prioritization and balancing technique, wherein, in response to a processing task, the first and second HPC ECUs each obtain a set of inputs indicative of parameters of the distributed mesh network, the first and second HPC ECUs each execute the load prioritization and balancing technique based on the set of inputs to obtain a desired processing allocation of the processing task between the first and second HPC ECUs, and the first and second HPC ECUs execute the processing task according to the desired processing allocation to obtain and output a final result for the processing task.

Abstract: A three-dimensional (3D) image projection system for a vehicle includes a memory having a trained holographic interference machine learning model stored thereon and an electronic control unit (ECU) of the vehicle comprising a central processing unit (CPU), a graphical processing unit (GPU), and a neural processing unit (NPU), wherein the NPU is configured to access, via the memory, the trained holographic interference machine learning model and, in response to a request for projection of a 3D image, utilize the trained holographic interference machine learning model to generate a holographic interference pattern image for the 3D image projection.

Abstract: A vehicle includes a sensor system including one or more individual sensors configured to capture sensor data, a driver camera configured to monitor a driver head position and a driver gaze vector indicating a direction of driver vision, and a data compression system including a computing device. The computing device is configured to perform operations including: receiving sensor data from each individual sensor, determining, by the driver camera, an instantaneous driver head position and driver gaze vector, determining, for each individual sensor, a region of interest (ROI) of the sensor data based on the instantaneous driver head position and driver gaze vector, and cropping the ROI for each individual sensor based on an intersection of the driver gaze vector with the determined ROI to thereby provide cropped sensor data with a reduced amount of sensor data from each individual sensor.

Abstract: A vehicle camera system configured for both human vision and machine vision functionality includes an image sensor defining an array of photovoltaic cells each configured to detect light and output an unfiltered array of light samples, a red/green/clear/blue (RGCB) color filter array (CFA) configured to color filter the unfiltered array of light samples and output an array of color samples, and a control system configured to apply a first interpretation technique to the array of color samples to obtain a human vision image and apply a different second interpretation technique to the array of color samples to obtain a machine vision image having a reduced color space and improved transmittance compared to the human vision image, wherein the second interpretation technique involves utilizing each clear value as a luminance value in the determination of red/green/blue values for each color sample.

Abstract: An automotive heads-up display (HUD) calibration system includes a back-lit HUD system of an automobile, the back-lit HUD system being configured for full array local dimming (FALD) via a plurality of independently-controlled back-lit regions, and a computing system configured to optimize a set of graphics for projection by the back-lit HUD system to reduce energy consumption by the FALD control of the back-lit HUD system, where the computing system is an external computing system that is only associated with the back-lit HUD system temporarily in a calibration environment.

Abstract: A heads-up display (HUD) system for an automobile includes a projection system configured to project a warped image onto a reflective portion of a surface of a windshield of the automobile, wherein the windshield surface defines a curvature such that the reflected projected warped image appears substantially non-warped to a driver of the automobile and a control system comprising a neural processing unit (NPU) configured to execute a set of machine learning based tasks of the automobile, including obtaining a trained warping model configured for warping an image to obtain the warped image and executing the trained warping model on the image to obtain the warped image, wherein the control system does not utilize a graphical processing unit (GPU) to warp the image or to otherwise obtain the warped image.

Abstract: A vehicle information display assembly comprises a digital display including a plurality of tell-tales, a first illumination source to provide light to the display, a light guide to transmit the light from the first illumination source to the digital display in an even manner, wherein the light guide defines a plurality of apertures each in a region of one of the plurality of tell-tales, and a plurality of second illumination sources, each proximate to one of the plurality of apertures in the light guide such that one of the plurality of second illumination sources may be activated when a corresponding one of the plurality of tell-tales is activated. A method of communicating information relating to a vehicle operating parameter, and a vehicle information display assembly are also disclosed.

Abstract: A method of providing full array local dimming to a display comprises performing an image processing algorithm with a processor having instructions for: determining a new pixel value for each of a plurality of pixels of the image, mapping the new pixel value to a prior pixel value for each of the plurality of pixels, scaling the image of the zone bilinearly, repeating the determining mapping and scaling until an approximation value is reached, compiling the repeated results into a data set. The method also includes dividing an image for the display having into a plurality of zones each having at least one LED associate therewith and making an illumination decision from the data set, where the illumination decision is for the at least one LED associated with one of the plurality of zones.

Abstract: A LiDAR sensor includes a light emitter, a spatial light modulator positioned to direct light from the light emitter into a field of illumination, and a light detector having a field of view overlapping the field of illumination. The LiDAR sensor includes a controller programmed to identify an area of interest based on light detected by the light detector in a previous subframe and adjust the spatial light modulator to direct light into the field of illumination at an intensity that is greater at the area of interest than at an adjacent area of the field of view.

Abstract: A head up display assembly includes an optical system (52) and a transmissive display. A light source is configured to projected a light through the transmissive display. A diffuser (64) is located between the optical system and the transmissive display (62).

Abstract: A method of providing image includes obtaining at least one first image of a surrounding area (52) from a first camera (26, 33, 38A, 38B, 40A, and 40B). At least one second image of the surrounding area (52) is obtained from a second camera (26, 33, 38A, 38B, 40A, and 40B). The at least one first image is fused with the at least one second image to generate a three-dimensional model (51) of the surrounding area (52). A first image (54A) of the three dimensional model is provided to a display by determining a first position of an operator. A second image (54B) of the three-dimensional model is provided to the display by determining when the operator is in a second position to simulate motion parallax.

Abstract: A head up display assembly includes an optical system (52) and a transmissive display. A light source is configured to projected a light through the transmissive display. A diffuser (64) is located between the optical system and the transmissive display (62).

Abstract: Various embodiments of an augmented reality alignment system and method are disclosed. An exemplary alignment system and method therefor may correct for image misalignment, distortion, and image deflection of graphic images that are projected within an operator's field of view. The alignment system may be configured to consider a number of dynamic and static error factor inputs in real time such that when a graphic image is projected, the graphic image is substantially aligned with the real-world target it is intended to overlay and the graphic image is displayed substantially free of distortion.

Abstract: Various embodiments of an augmented reality alignment system and method are disclosed. An exemplary alignment system and method therefor may correct for image misalignment, distortion, and image deflection of graphic images that are projected within an operator's field of view. The alignment system may be configured to consider a number of dynamic and static error factor inputs in real time such that when a graphic image is projected, the graphic image is substantially aligned with the real-world target it is intended to overlay and the graphic image is displayed substantially free of distortion.

Abstract: Various embodiments of an augmented reality alignment system and method are disclosed. An exemplary alignment system and method therefor may correct for image misalignment, distortion, and image deflection of graphic images that are projected within an operator's field of view. The alignment system may be configured to consider a number of dynamic and static error factor inputs in real time such that when a graphic image is projected, the graphic image is substantially aligned with the real-world target it is intended to overlay and the graphic image is displayed substantially free of distortion.