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: Wrong way travel detection and control systems and methods for a vehicle utilize a set of perception sensor systems each configured to perceive a position of the vehicle relative to its environment, a map system configured to maintain map data, and a controller configured to receive first information from the set of perception sensor systems and the map system, generate a confidence score indicative of a likelihood that the vehicle is traveling in a wrong direction along a roadway using a vehicle position model and the received first information, compare the confidence score to a set of one or more thresholds, and based on the comparing, selectively control one or more operating parameters of the vehicle to remedy the wrong direction travel of the vehicle.

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.