A method for illuminating vehicle surroundings of a motor vehicle that comprises an illumination device and a detection device, wherein the illumination device is set up to illuminate at least part of a solid angle region of the vehicle surroundings with different illumination patterns, in particular with visible light, wherein the illumination patterns each predefine illumination intensities for different solid angle subregions of the solid angle region, comprising the steps of: illuminating the vehicle surroundings with a first of the illumination patterns by means of the illumination device, detecting a light pattern that results from the illumination of the vehicle surroundings with the first illumination pattern by means of the detection device, selecting a second of the illumination patterns on the basis of the detected light pattern, and illuminating the vehicle surroundings with the second illumination pattern by means of the illumination device.

A suspension monitoring and adjustment system for an off-road vehicle includes a distance sensor arranged to measure shock displacement of a suspension of the vehicle. The system may include an output device configured to output shock displacement data generated by the distance sensor and a processor or programmable circuit operable to produce a visual representation of the shock displacement data output by the output device. The system may include a processor or programmable circuit operable to generate an adjustment signal based on shock displacement data generated by the distance sensor and a suspension adjuster arranged to adjust the suspension of the vehicle in response to the adjustment signal.

This application relates to a suspension control method and system, a vehicle, and a storage medium. The suspension control method includes: acquiring a pavement image in a traveling direction; identifying a variation type corresponding to a pavement smoothness variation according to the pavement image; generating a control signal according to the identified variation type, to adjust a suspension parameter; detecting, by using a sensor coupled to a suspension, pavement characteristic information corresponding to the variation type; and generating a correction signal based on the pavement characteristic information, to correct the control signal. The suspension control method can identify the pavement smoothness variation more accurately and set the suspension damping parameter according to an identification result.

A milling machine may have a frame, a milling drum attached to the frame, and ground engaging tracks that support the frame and propel the milling machine in a forward or rearward direction. The milling machine may have height adjustable actuators connecting the frame to the tracks. Each actuator may have a cylinder attached to the frame, a piston slidably disposed within the cylinder, and a rod connected at a first end to the piston and connected to a track at a second end. The milling machine may have a tank storing hydraulic fluid and a fluid conduit connecting the tank to the cylinder. The milling machine may have a control valve selectively controlling a flow rate of the hydraulic fluid in the fluid conduit. The milling machine may also have a controller that determines a height of the frame relative to the ground surface based on the flow rate.

Disclosed are a system, a method, and an apparatus for controlling a suspension using image data captured by an image sensor. The suspension control apparatus includes at least one image sensor mounted to an own vehicle to capture image data of the surrounding environment of the own vehicle, and a controller configured to control the own vehicle based on the image data captured by the at least one image sensor, wherein the controller receives the image data from the at least one image sensor, extracts suspension control reference information including at least one of road environment information, own vehicle surrounding object information, and own vehicle state information based on the image data and/or an in-vehicle sensor of the own vehicle, and generates a control signal for controlling the height of a suspension according to the suspension control reference information.

The disclosure relates to a method for determining object information relating to an object in an environment of a multi-part vehicle having at least one towing vehicle and at least one trailer and a control unit and vehicle associated with it, with at least one trailer camera being arranged on the trailer, having at least the following steps: capturing the environment with a trailer camera from a first position and, in dependence thereon, creating a first image having first pixels; changing the position of the trailer camera; capturing the environment with the trailer camera from a second position and creating a second image having second pixels; and, determining object information relating to an object in the captured environment.

A self-calibrating scanning system and method provides a novel way to eliminate errors in scanning systems, such as lidar or radar detection, using an inertial measurement unit. The system includes an energy transmission source configured to transmit an energy signal through a transmittal area. A detector receives a return energy signal of at least one target object of the energy transmitter source within the transmittal area. The system calculates at least one of the range and position of an object from information relating to at least one of the time and phase of the return energy signal relative to the transmittal energy signal. The spatial or angular displacement of the detector relative to the light source is measured using data from the inertial measurement unit, and at least one of calculated range and position of the object is adjusted based on the spatial or angular displacement of the detector.

This application relates to an electronically controlled air suspension (ECAS) system. When a vehicle starts, the ECAS system receives data from a wheel height sensor and sets the received height as a default height. When driving, a high-speed line profiler scans the road surface in front of the tires of the vehicle. This information is processed by an image processing unit to determine the amount of air in the corresponding damper. If there is a bump on the road, the ECAS system may reduce the amount of air on the tire side in advance, and if there is a dip, the ECAS system may increase the amount of air on the tire side in advance to minimize vibration. Regarding the residual vibration after passing through the bump or dip, the amount of air is adjusted so that the vibration stops quickly by receiving real-time data from the wheel height sensor.

In some embodiments, methods and systems may be used to control operation of various systems of the vehicle based on road features included in an upcoming portion of a road surface located along a path of travel of the vehicle. This control may either be based on a probability of encountering a road feature on the road surface 5 and/or frequency information related to the upcoming portion of the road surface.

The present disclosure relates to a method and an apparatus for controlling an electronic control suspension using a deep learning-based road surface classification model. The method for controlling an electronic control suspension in a vehicle including a camera and a GPS receiver may include collecting location information of the vehicle using the GPS receiver while driving, identifying whether there is a previously generated road surface classification model corresponding to a front obstacle when the front obstacle is detected, determining a first control value based on a first characteristic value corresponding to the road surface classification model when there is the road surface classification model as a result of the identification, controlling the electronic control suspension with the determined first control value when entering the obstacle, and collecting new sensing data through a physical sensor, and correcting the first characteristic value based on the new sensing data.