Vehicle center of gravity (CoG) height and mass estimation techniques utilize a light detection and ranging (LIDAR) sensor configured to emit light pulses and capture reflected light pulses that collectively form LIDAR point cloud data and a controller configured to estimate the CoG height and the mass of the vehicle during a steady-state operating condition of the vehicle by processing the LIDAR point cloud data to identify a ground plane, identifying a height difference between (i) a nominal distance from the LIDAR sensor to the ground plane and (ii) an estimated distance from the LIDAR sensor to the ground plane using the processed LIDAR point cloud data, estimating the vehicle CoG height as a difference between (i) a nominal vehicle CoG height and the height difference, and estimating the vehicle mass based on one of (i) vehicle CoG metrics and (ii) dampening metrics of a suspension of the vehicle.

The invention provides a vehicle control method and device, a computer storage medium, and a vehicle, which are applied to the technical field of automobiles. The vehicle control method includes: determining, based on first information, second information, and third information, whether a vehicle is performing a reverse parking maneuver; comparing a reversing speed with a predetermined first speed when the vehicle is performing the reverse parking maneuver; and if the reversing speed is higher than the predetermined first speed, outputting a first control signal to adjust the reversing speed such that the reversing speed is not higher than the predetermined first speed, where the first information includes information indicating that the vehicle is in reverse gear, the second information indicates an environment surrounding the vehicle, and the third information indicates that the reversing speed is lower than a predetermined second speed, where the predetermined first speed is lower than the predetermined second speed.

In some examples, a vehicle suspension for supporting, at least in part, a sprung mass, includes a damper connected to the sprung mass, the damper including a movable piston. The vehicle suspension further includes an actuator and a controller. The controller may be configured to determine a frequency of motion associated with the sprung mass. When the frequency of motion is below a first frequency threshold, the controller may send a control signal to cause the actuator to apply a deceleration force to the sprung mass. Further, when the frequency of motion associated with the sprung mass exceeds the first frequency threshold, the controller may send a control signal to cause the actuator to apply a compensatory force to the sprung mass. For instance, a magnitude of the compensatory force may be based on a friction force determined for the damper.

A travel instruction information generation device has a vehicle information acquisition unit, a travel instruction information generator, and a correction information generator. The vehicle information acquisition unit acquires vehicle information representing a specific state of a vehicle. The travel instruction information generator generates travel instruction information with which the vehicle performs self-driving by using three-dimensional map information. The correction information generator generates, on the basis of the vehicle information, correction information for correcting the travel instruction information.

Vehicle center of gravity (CoG) height and mass estimation techniques utilize a light detection and ranging (LIDAR) sensor configured to emit light pulses and capture reflected light pulses that collectively form LIDAR point cloud data and a controller configured to estimate the CoG height and the mass of the vehicle during a steady-state operating condition of the vehicle by processing the LIDAR point cloud data to identify a ground plane, identifying a height difference between (i) a nominal distance from the LIDAR sensor to the ground plane and (ii) an estimated distance from the LIDAR sensor to the ground plane using the processed LIDAR point cloud data, estimating the vehicle CoG height as a difference between (i) a nominal vehicle CoG height and the height difference, and estimating the vehicle mass based on one of (i) vehicle CoG metrics and (ii) dampening metrics of a suspension of the vehicle.

The invention relates to a method for operating a motor vehicle, which has a contactless head-up display, kHUD, which is designed to display virtual contents in superposition with real objects, and furthermore has a semi-active damper system, which is designed to be operated selectively with one of a plurality of damper characteristic curves. In the method according to the invention, a real object located in the direction of travel of the motor vehicle is identified, and virtual content for augmenting the identified real object is determined. In order to prepare for the display of the virtual content, one of the plurality of damper characteristic curves of the semi-active damper system is then selected in order, for example, to optimize both the operation and simulation of the damper system. The virtual content is then displayed, by means of the kHUD, in superposition with the real object, with fewer spatial discrepancies.

In some examples, a vehicle suspension for supporting, at least in part, a sprung mass, includes a damper connected to the sprung mass, the damper including a movable piston. The vehicle suspension further includes an actuator and a controller. The controller may be configured to determine a frequency of motion associated with the sprung mass. When the frequency of motion is below a first frequency threshold, the controller may send a control signal to cause the actuator to apply a deceleration force to the sprung mass. Further, when the frequency of motion associated with the sprung mass exceeds the first frequency threshold, the controller may send a control signal to cause the actuator to apply a compensatory force to the sprung mass. For instance, a magnitude of the compensatory force may be based on a friction force determined for the damper.

A vehicle may include an active ride comfort tuning system that reactively and/or proactively alters a parameter of a system of the autonomous vehicle to mitigate or avoid interruptions to ride smoothness. For example, the comfort tuning system may alter a parameter of a drive system, suspension, and/or a trajectory cost function. The comfort tuning system may alter the parameter based at least in part on detecting and/or receiving a comfort indication, determined based on sensor data, user input, or the like.

A device for reducing noise in an interior space of a vehicle is provided. The vehicle includes a body having the interior space, at least one tire, and one wheel rim associated with the tire. The tire and the wheel rim are mounted onto a suspension strut, and the suspension strut is mounted onto the body. The device is arranged outside the interior space of the vehicle. The device includes a sound determination unit and a sound reduction unit. The sound determination unit includes a sensor configured for determining structure-borne noise. The sound reduction unit is configured for generating a vibration.

The invention concerns a method for estimating an International Roughness Index (IRI) of a road or road segment. comprising a preliminary step (1) and an International Roughness Index estimation step (10). The preliminary step (1) comprises collecting (2) values of vehicle tire damping and stiffness coefficients (C.sub.t, K.sub.t) and collecting (3) vehicle vertical acceleration values (Az.sub.vehicle) measured on vehicles driven at a constant speed along road segments to which known international roughness index values or known road profiles (profile.sub.r) are associated, as well as vehicle geo-referencing data and speed data indicative of the given constant speed associated with the measured vertical acceleration values (Az.sub.vehicle).