A method, device, and computer-readable storage medium with instructions for controlling a display of an augmented-reality head-up display device for a transportation vehicle. A position of the transportation vehicle is determined relative to a map; at least one reference point is extracted from the map, the at least one reference point is obtained from an area within a visual range of a driver of the transportation vehicle; transforming the at least one reference point into transportation vehicle coordinates; generating a virtual object for display by the augmented-reality head-up display device, considering the at least one transformed reference point; and outputting the virtual object for display by the augmented-reality head-up display device.

Disclosed are a display device linked to a vehicle and an operating method thereof. More specifically, the display device may communicate with a system to display AR digital signage on a building in a driving image of the vehicle on a floor-by-floor basis. Also, by mapping and displaying AR digital signage that has been displayed on the building on a floor-by-floor basis on an AR carpet displayed on a road in the driving image while the vehicle is about to or is expected to enter the building, it is possible to significantly enhance visibility and ensure safe driving.

Devices, systems, and methods related to autonomous transportation vehicle operation may include image augmentation arrangements for training and/or evaluating autonomous operations. Such augmentations may include artificial impressions of driving conditions which can prompt recovery operations.

Systems and methods are provided for generating trajectories for a vehicle user interface showing a driver's perspective view. Methods include generating an ego-vehicle predicted trajectory for an ego-vehicle; and generating at least one road agent predicted trajectory for a road agent that is external to the ego-vehicle. After the predicted trajectories are generated, the method continues by determining that at least two predicted trajectories overlap when displayed on the user interface showing a driver's perspective view, when displayed on the user interface showing a driver's perspective view. The method includes modifying the at least one road agent predicted trajectory to remove the overlap. The method then proceeds with updating a display of the user interface to include any modified road agent predicted trajectory. Systems include a trajectory-prediction module to execute the methods.

Disclosed is a system of providing a parking guidance service of a vehicle including a sensor unit including a plurality of sensors configured to sense an environment around the vehicle and a parking space, a database unit configured to store parking pattern data of a driver, a controller configured to determine a parking difficulty of the parking space based on information sensed by the sensor unit and parking pattern data of the driver, stored in the database unit, and an output unit configured to provide information on the parking difficulty of the parking space, determined by the controller.

An apparatus, method and system utilize an unmanned air vehicle (UAV) in order to support the definition and use of routes by bicyclists, pedestrians or scooters. With respect to defining a bicycle route a map database is accessed that represents roads segments in a geographic area. The map database contains map data that indicates attributes of the road segments. The bicycle route is then defined from an origin to a destination based upon the map data indicative of attributes of the road segments. In this regard, the bicycle route is defined to include one or more road segments that allow bicycle traffic unaccompanied by a UAV and one or more road segments for which bicycle traffic is unauthorized unless accompanied by a UAV. The bicycle route is subsequently caused to be provided to the bicyclist or a device accessible to the bicyclist.

A display control device mounted on a vehicle: determines whether a caution point exists in front of a vehicle; determines whether the caution point is included in an angle of view of a head-up display mounted on the vehicle; displays a caution content as a superimposed content with the caution point as a superimposition target in response to the caution point being determined to be included in the angle of view; displays the caution content as a non-superimposed content with no superimposition target in response to the caution point being determined to be not included in the angle of view; determines a type of the caution point; displays the caution content associated with the determined type of the caution point.

A system and method may generate a more realistic augmented reality (AR) overlay by generating a segmentation image and blending it with one or more other images. The system may generate a segmentation image based on an input image. The segmentation image may be blended with an AR path overlay image to generate an object-masked AR path overlay image. The object-masked AR path overlay image may be blended with the input image to generate an output image.

Based on information about a vehicle, the information can be projected and displayed onto a road surface or the like. An image projection apparatus, which projects an image, includes an acquisition unit that acquires the information about the vehicle, and an image projection unit that projects the image based on the information acquired by the acquisition unit.

Disclosed herein are a head-up display (HUD) including a photosensor for measuring the illuminance of incoming light and a light shutter in order to protect an imaging element vulnerable to thermal damage from sunlight reaching from the outside, and a method including setting the HUD protection mode by operating the light shutter, determining whether to release the HUD protection mode by estimating the change in the incident angle of the incoming light from the change in the vehicle orientation angle instead of using the photosensor incapable of measuring the light as the incoming light is blocked and additionally determining whether to release the HUD protection mode based on vehicle information including vehicle location, navigation map information, the brightness of surroundings of the vehicle, and rain sensor detection information.