An assistance system includes: an augmented reality module configured to i) determine a path of a host vehicle, ii) detect one or more objects with one or more trajectories predicted to interfere with the path of the host vehicle, and iii) based on the one or more trajectories, generate a first digital gateway indicative that the host vehicle should yield for the one or more objects; a display control module configured to control an augmented reality head-up display to display the first digital gateway in a closed state over an environment forward of the host vehicle and along the path of the host vehicle; and a vehicle control module configured to yield to the one or more objects as the host vehicle approaches the first digital gateway.

A system for gaze-based control of vehicle functions and related methods includes eye contact sensors for monitoring one or both eyes of a user, manual input devices, and circuits configured for tracking a gaze of a user located within a vehicle, identifying a gaze condition from the eye contact sensors in response to determining the gaze of the user is directed to an object of interest in the vehicle for at least a predetermined dwell-time, receiving a manual input from the manual input devices, activating a command interaction associated with the object of interest in response to identifying the gaze condition and receiving the manual input, receiving, while the command interaction is active, a command associated with the object of interest from the user, and initiating a vehicle function based on the received command.

A system for gaze-based control of vehicle functions and related methods includes eye contact sensors for monitoring one or both eyes of a user, manual input devices, and circuits configured for tracking a gaze of a user located within a vehicle, identifying a gaze condition from the eye contact sensors in response to determining the gaze of the user is directed to an object of interest in the vehicle for at least a predetermined dwell-time, receiving a manual input from the manual input devices, activating a command interaction associated with the object of interest in response to identifying the gaze condition and receiving the manual input, receiving, while the command interaction is active, a command associated with the object of interest from the user, and initiating a vehicle function based on the received command.

A head-up display includes a housing; a screen disposed in the housing, the screen including a Fresnel pattern and facing a windshield; an illumination optical module configured to generate and irradiate light; an image generator configured to receive the light irradiated from the illumination optical module and generate image light; and a projection optical module configured to project the image light generated from the image generator onto the screen, wherein an upper surface of the screen faces a rearward upper direction away from the windshield or a forward upper direction toward the windshield according to an angle of the windshield with respect to a horizontal plane, and wherein a curvature of the Fresnel pattern of the screen is directly proportional to the angle of the windshield.

A head-up display includes a housing; a screen disposed in the housing, the screen including a Fresnel pattern and facing a windshield; an illumination optical module configured to generate and irradiate light; an image generator configured to receive the light irradiated from the illumination optical module and generate image light; and a projection optical module configured to project the image light generated from the image generator onto the screen, wherein an upper surface of the screen faces a rearward upper direction away from the windshield or a forward upper direction toward the windshield according to an angle of the windshield with respect to a horizontal plane, and wherein a curvature of the Fresnel pattern of the screen is directly proportional to the angle of the windshield.

A method is provided for visualizing optical information in the central field of vision of a driver in such a way that a display (5) in the form of a virtual image is superimposed on a real traffic environment. A position of the display (5) is dynamically variable as a function of a vehicle speed, a steering angle, and a road type. Thus a horizontal and/or vertical spread of a display range (8) between a first maximum value (9) and a second maximum value (10) within which the display (5) can be displayed is varied as a function of speed, steering angle and roadway type.

A circuit device includes a storing section configured to store a rendering image and a warp processing section. The warp processing section includes a coordinate converting section, a coordinate-address converting section, and an output section. The coordinate converting section converts, with coordinate conversion based on warp parameters and rotation correction parameters, an output coordinate, which is a coordinate on a display image, into an input coordinate, which is a coordinate on the rendering image. The coordinate-address converting section converts the input coordinate into a read address of the storing section. The output section reads out pixel data of the rendering image from the read address of the storing section and outputs, based on the read-out pixel data, pixel data in the output coordinate of the display image.

A system for training a machine learning algorithm to generate a plurality of ideal hologram phase correction maps includes a holographic head-up display (HUD) configured to display a plurality of duplicates of a graphic based on a hologram phase map. The system further includes a camera system configured to view each of the plurality of duplicates of the graphic. The system further includes a controller in electrical communication with the holographic HUD and the camera system. The controller is programmed to determine a plurality of ground-truth hologram phase correction maps using a genetic algorithm, the holographic HUD, and the camera system. The controller is further programmed to generate a training dataset including a plurality of images of the graphic and train the machine learning algorithm to generate the plurality of ideal hologram phase correction maps.

A head up display arrangement for a motor vehicle includes a picture generation unit emitting a light field along a projection path. At least one mirror is positioned to reflect the light field emitted by the picture generation unit such that the reflected light field is again reflected by a windshield of the motor vehicle so as to be visible by a human driver of the motor vehicle as a virtual image. A camera is positioned to capture images along the projection path. An electronic processor is communicatively coupled to the camera and analyzes the images captured by the camera to thereby determine whether there is an obstruction in the projection path. The electronic processor notifies the human driver of the obstruction if it is determined that there is an obstruction in the projection path.

A head up display arrangement for a motor vehicle includes a picture generation unit emitting a light field along a projection path. At least one mirror is positioned to reflect the light field emitted by the picture generation unit such that the reflected light field is again reflected by a windshield of the motor vehicle so as to be visible by a human driver of the motor vehicle as a virtual image. A camera is positioned to capture images along the projection path. An electronic processor is communicatively coupled to the camera and analyzes the images captured by the camera to thereby determine whether there is an obstruction in the projection path. The electronic processor notifies the human driver of the obstruction if it is determined that there is an obstruction in the projection path.