A method for controlling a vehicle that includes at least one camera and a lamp, the method including: controlling the at least one camera to capture at least one image of an area in front of the vehicle; extracting, from the at least one image, a light distribution pattern formed by the lamp in the area in front of the vehicle; and performing at least one control related to the extracted light distribution pattern, based on a comparison result obtained by comparing the extracted light distribution pattern with a reference light distribution pattern.

A system may have lights. The lights may be moved using a positioner. Control circuitry may use sensor circuitry to monitor the environment surrounding the system. The sensor circuitry may include one or more sensors to measure the shape of a surface in front of the system and the location of the surface relative to the system. The sensor circuitry may also measure light illumination on the surface. Based on the known shape of the surface in front of the system and the distance of the surface from the system, the control circuitry can predict where a light should be aimed on the surface. By comparing predictions of light illumination on the surface to measurements of light illumination on the surface, the system can determine how to move the light with the positioner to align the light.

An ADAS calibration system for calibrating at least one headlamp of a vehicle. The ADAS calibration system including a support; optical measurement device mounted on the support for detecting the distances of two front or rear wheels of the vehicle from the support; a projection surface mounted on the support; and at least one headlamp beam setter. The headlamp beam setter includes a screen configured to show a pattern created by the two-dimensional projection of the light beam emitted by the headlamp and a camera configured to acquire images of the pattern shown on the screen. The ADAS calibration system also includes a control unit configured to receive from the optical measurement device the distances detected and from the camera the images of the pattern and, in response to them, to compute an alignment angle for the headlamp.

A method for verifying an alignment of one or more devices of a vehicle in a manufacturing environment includes selecting an alignment verification routine to be performed by an autonomous alignment verification mobile robot (AAVMR) and autonomously positioning the AAVMR based on a position of the vehicle and one or more displacements associated with the alignment verification routine. The method includes performing, using the AAVMR, the alignment verification routine to generate one or more alignment characteristics associated with the one or more devices and broadcasting a notification based on the one or more alignment characteristics.

A method for analyzing a light emission of a headlight of a vehicle includes: a step of reading in a distance which represents a distance between the vehicle and an object situated in the surroundings of the vehicle; a step of reading in an illumination value which represents a height of an area of the object which is illuminated by the light emission; and a step of determining a light emission value which characterizes the light emission, using the distance value and the illumination value.

A vehicle headlamp aiming system includes a displaceable aiming surface and an imaging system. The imaging system includes an indexing aim box having at least one imager oriented to capture images of a headlamp and/or one or more vehicle features adjacent to the headlamp and at least one fixed imager oriented to capture one images of the displaceable aiming surface to determine a headlamp cutoff height. The displaceable aiming surface is configured to selectively displace to allow passage of the vehicle. The indexing aim box is configured to translate between the headlamp and another headlamp. One or more computing devices are configured to perform methods for headlamp aim correction using the described system. The methods include providing image inputs from the imaging system and calculating therefrom an aim correction of the headlamps.

A method for verifying an alignment of one or more devices of a vehicle in a manufacturing environment includes selecting an alignment verification routine to be performed by an autonomous alignment verification mobile robot (AAVMR) and autonomously positioning the AAVMR based on a position of the vehicle and one or more displacements associated with the alignment verification routine. The method includes performing, using the AAVMR, the alignment verification routine to generate one or more alignment characteristics associated with the one or more devices and broadcasting a notification based on the one or more alignment characteristics.

A calibration method includes forming a calibration pattern with a light distribution variable lamp onto a screen located at a distance from the light distribution variable lamp and an imaging device, capturing an image of the calibration pattern with the imaging device, acquiring a correspondence relationship between position coordinates of an image captured by the imaging device and position coordinates of the calibration pattern in a light illumination range, calculating an amount of parallax difference between the light distribution variable lamp and the imaging device, and correcting the correspondence relationship based on the amount of parallax difference and generating mutual position information between the light illumination range and the imaging range.

A system for aiming a headlamp of a vehicle includes a displaceable aiming surface and an imaging system. The imaging system includes a translatable aim box carrying at least one headlamp imager oriented to capture images of a single headlamp and/or one or more vehicle features adjacent to the single headlamp. At least one fixed imager is oriented to capture one or more images of the displaceable aiming surface. The translatable aim box may be configured to translate between the single headlamp and another headlamp. One or more computing devices are configured to perform methods for headlamp aim correction using the described system. Methods for headlamp aim correction are described.

A vehicle headlamp device includes headlamps, which are structured so as to be able to project or irradiate given patterns and given shapes without distortion on a given virtual surface in front of a vehicle from a left headlight and a right headlight, respectively, a camera that captures an image of the area in front of the vehicle, and a state detecting portion configured to detect distortion of the given patterns, which are projected or irradiated on an irradiated surface in front of the vehicle, relative to the given patterns projected or irradiated on the given virtual surface in front of the vehicle, based on the captured image, and also detect a state of the irradiated surface based on the distortion, and a correcting portion configured to correct a relative optical axis deviation between the left headlight and the right headlight.