A raindrop recognition device is configured to recognize a raindrop on a transparent panel. The raindrop recognition device includes a storage unit, an image input unit, and an image recognition unit. The storage unit stores a trained model that is a machine learning model trained using, as training data, images of the transparent panel with adhered raindrops and images of the transparent panel without adhered raindrops. Image data of the transparent panel taken by a camera is input to the input unit. The image recognition unit is configured to calculate a value representing a raindrop likeness of an object on the transparent panel in the image data by inputting the image data to the trained model. The trained model is trained by training data including images of the transparent panel with uniform background and images of the transparent panel with light source.

The present invention relates generally to the field of camera covers. More specifically, the present invention relates to a vehicle camera cover for exterior cameras of a vehicle. The cover is comprised of a base that is further comprised of a padded magnet or adhesive layer that allows the cover to magnetically or adhesively attach to the exterior surface of a vehicle. A magnetic base layer with a magnetic bottom surface further attaches to the top surface of the magnet layer, and is comprised of a hinge. A transparent lid further attaches to the hinge, wherein the outer surface of the hinge is comprised of a water-repelling coating. Therefore, the cover ensures precipitation or debris cannot obstruct, cover, or damage the exterior cameras of a vehicle, and wherein the cover can be removed as desired without damaging the exterior vehicle surface.

A vehicular windshield wiper control system includes a camera disposed at a vehicle and viewing through a windshield of the vehicle and an electronic control unit (ECU). Electronic circuitry of the ECU includes an image processor. The system, based on processing of image data captured by the camera, is operable to determine presence of a substance at an outer surface of the windshield. The system includes a windshield wiper having a rubber wiping blade and a cleaning element. The system is operable to (i) cause the rubber wiping blade to engage the windshield and/or (ii) cause the cleaning element to engage the windshield. Responsive to determining presence of the substance, the system causes the cleaning element to engage the windshield. With the rubber wiping blade and/or cleaning element engaging the outer surface of the windshield, the system moves the rubber wiping blade and/or cleaning element along the windshield.

An apparatus, method and computer program product are provided for determining a state of visibility of a road object, such as a road sign, using vehicle sensor data. For example, the apparatus determines whether one or more sensors of a first vehicle observes a road sign. If the road sign is not observed by the one or more sensors, the apparatus determines whether one or more second vehicles is obscuring the road sign. If the one or more second vehicles is not obscuring the road sign, the apparatus determines whether the road sign is obscured due to a weather condition. If the road sign is obscured due to the weather condition, the apparatus generates a signal indicating that the road sign was obscured due to the weather condition.

An apparatus and a method for controlling an autonomous vehicle depending on weather are provided. The apparatus obtains information including at least one of an image around the autonomous vehicle, sensing information of a Light Detection and Ranging (LiDAR) of the autonomous vehicle, sensing information of a rain sensor of the autonomous vehicle, an operation state of a windshield wiper of the autonomous vehicle, climate information through vehicle to everything (V2X) communication, an acceleration of the autonomous vehicle, or wheel sensor information of the autonomous vehicle and determines whether the climate state is an inclement weather state, based on the information including the at least one of the image around the autonomous vehicle, the sensing information of the LIDAR, the sensing information of the rain sensor, the operation state of the windshield wiper, the climate information through the V2X communication, the acceleration, or the wheel sensor information.

The present disclosure relates to a speckles detection system for detecting one or more speckles on a surface of an optical element of an image capturing device. The system comprises: one or more light sources configured to emit a light beam towards the optical element, the optical element being configured to reflect light from the light sources when speckles are located on the surface of the optical element. The system further comprises one or more light receivers configured to receive the light beam reflected by the optical elements such that speckles on the surface of the optical elements are detected. Methods for detecting one or more speckles on a surface of an optical element of an image capturing device are also provided.

The present disclosure relates to a speckles detection system for detecting one or more speckles on a surface of an optical element of an image capturing device. The system comprises: one or more light sources configured to emit a light beam towards the optical element, the optical element being configured to reflect light from the light sources when speckles are located on the surface of the optical element. The system further comprises one or more light receivers configured to receive the light beam reflected by the optical elements such that speckles on the surface of the optical elements are detected. Methods for detecting one or more speckles on a surface of an optical element of an image capturing device are also provided.

A system and method of automatically activating a windshield wiper system of a vehicle having a front windshield with a front wiper and a rear windshield with a rear wiper are provided. The method comprises assessing at least one windshield classification of road conditions based on original information and capturing a front image of the front windshield, a rear image of the rear windshield, and an environment image of the environment. The method further comprises classifying the images to define a first windshield class. The method further comprises determining a front windshield perception, a rear windshield perception, and an environment perception of the first windshield class to define a first combination of detection sources. The method further comprises fusing the front windshield perception, the rear windshield perception and the environment perception, defining a first front probability of the first windshield class. The method further comprises activating the front wiper when the first front probability is greater than a front threshold.

An apparatus, method and computer program product are provided for determining a state of visibility of a road object, such as a road sign, using vehicle sensor data. For example, the apparatus determines whether one or more sensors of a first vehicle observes a road sign. If the road sign is not observed by the one or more sensors, the apparatus determines whether one or more second vehicles is obscuring the road sign. If the one or more second vehicles is not obscuring the road sign, the apparatus determines whether the road sign is obscured due to a weather condition. If the road sign is obscured due to the weather condition, the apparatus generates a signal indicating that the road sign was obscured due to the weather condition.

The present disclosure relates to methods and systems for generating a trained learning algorithm configured to predict the presence of environmental conditions in image data, a vehicle for utilizing the algorithm, as well as methods and systems for generating the training data for the automated supervised training of a learning algorithm. In some embodiments the training data is in the form of labelled images generated by a camera device arranged on a vehicle, where the labels are indicative of an environmental sensor activation or deactivation signal, or a user-input signal which serve as a supervisory signal for the training of the learning algorithm.