A vehicular vision system includes an image processor and a camera that views through the windshield of the vehicle. The camera captures image data as the vehicle travels along a road, and the image processor processes image data captured by the camera. The vehicular vision system, responsive at least in part to processing by the image processor of image data captured by the camera, determines when the vehicle is at a construction zone. Responsive to determining that the vehicle is at the construction zone, the vehicular vision system adjusts a vehicular driver assistance system of the vehicle. The vehicular vision system determines that the vehicle exits the construction zone based at least in part on processing by the image processor of image data captured by the camera.

A vehicular control system includes a plurality of sensors that include at least a camera and a 3D point-cloud LIDAR. As the vehicle travels along a road, and responsive at least in part to processing at an electronic control unit of 3D point-cloud LIDAR data captured by the 3D point-cloud LIDAR, the vehicular control system (a) determines presence of a pedestrian or cross traffic vehicle present exterior of the vehicle that (i) is not on the road that is being travelled along by the vehicle and is approaching the road to cross the road ahead of the vehicle and (ii) is at least in the field of sensing of the 3D point-cloud LIDAR and (b) at least in part controls at least one vehicle function of the vehicle responsive at least in part to the determined presence of the pedestrian or cross traffic vehicle.

A headlamp for a motor vehicle is provided including a plurality of first light sources for a high beam, emitting light during operation of the headlamp, and a plurality of second light sources for a low beam, emitting light during operation of the headlamp. A first light guide is also provided, having a plurality of light entry surfaces arranged side by side for the light emitted from the first light sources and a first light exit surface. A second light guide is also provided, having a plurality of light entry surfaces arranged side by side for the light emitted from the second light sources and a second light exit surface. At least a first one of the light entry surfaces has a greater width in the direction in which the light entry surfaces are arranged side by side than at least a second one of the light entry surfaces.

A headlamp for a motor vehicle is provided including a plurality of first light sources for a high beam, emitting light during operation of the headlamp, and a plurality of second light sources for a low beam, emitting light during operation of the headlamp. A first light guide is also provided, having a plurality of light entry surfaces arranged side by side for the light emitted from the first light sources and a first light exit surface. A second light guide is also provided, having a plurality of light entry surfaces arranged side by side for the light emitted from the second light sources and a second light exit surface. At least a first one of the light entry surfaces has a greater width in the direction in which the light entry surfaces are arranged side by side than at least a second one of the light entry surfaces.

In order to provide an enhanced driver assistance system for a vehicle, a prediction of a movement of the third-party vehicle is determined based upon motion data relating to a third- party vehicle travelling in front which has moved out of a region of view of at least one sensor of the vehicle, or relating to an oncoming third-party vehicle which has not yet entered the region of view of the sensor, and based upon map data The driver assistance system is then operated on the basis of the prediction.

A power controller configured to fit in a circuit breaker panel powering one or more loads. The power controller is further configured to manage critical loads of the one or more loads each controlled by a component that is capable of being actuated by the power controller and operated from a smartphone via the power controller, wherein the critical loads need not be wired to a dedicated circuit breaker panel.

A vehicular light switch can change the mode of an exterior-illuminating light by rotating to different positions including an auto setting and a SMALL setting. If the position of the vehicular light switch is rotated to the SMALL setting, a momentary mechanism returns the position to the auto setting. If extravehicular brightness is less than a prescribed value and the position is rotated to the SMALL setting whilst the vehicle is stationary, a first light controller turns off a low-beam light, and turns on the low-beam light if the vehicle runs afterwards. If extravehicular brightness is less than a prescribed value and the position is rotated to the SMALL setting while the vehicle is running, a second light controller keeps the low-beam light turned on.

A system for implementing adaptive light distributions for an autonomous vehicle (comprises the autonomous vehicle, a control device, and a headlight associated with the autonomous vehicle. The control device receives sensor data from sensors of the autonomous vehicle, where the sensor data comprises an image of one or more objects on a road traveled by the autonomous vehicle. The control device determines that a light condition level on a particular portion of the image is less than a threshold light level. The control device adjusts the headlight to increase illumination on a particular part of the road that is shown in the particular portion of the image.

An in-vehicle device that displays a setting screen for setting a function of a vehicle includes a display control unit that displays a vehicle image which is an image of a vehicle having a plurality of light units on the setting screen and that changes the on-off state of each of the plurality of light units shown in the vehicle image, according to the function to be set of the vehicle.

In various examples, high beam control for vehicles may be automated using a deep neural network (DNN) that processes sensor data received from vehicle sensors. The DNN may process the sensor data to output pixel-level semantic segmentation masks in order to differentiate actionable objects (e.g., vehicles with front or back lights lit, bicyclists, or pedestrians) from other objects (e.g., parked vehicles). Resulting segmentation masks output by the DNN(s), when combined with one or more post processing steps, may be used to generate masks for automated high beam on/off activation and/or dimming or shading—thereby providing additional illumination of an environment for the driver while controlling downstream effects of high beam glare for active vehicles.