In this vehicle inspection system for inspecting the driving functionality of a vehicle that carries out automatic driving or driving assistance, when a monitor and the vehicle are being aligned on a bench testing machine, a simulator device displays an image of a straight road on the monitor, a wheel sensor (wheel position sensor) detects the steering direction of a wheel (front wheel) steered using a lane keeping function, and an image position adjustment device (monitor position adjustment device) moves the image in the opposite direction from the steering direction of the wheel until the wheel reaches a neutral state of not being steered.

To obtain a vehicle control device capable of creating a route that facilitates tracing by a vehicle in autonomous driving and improving positional accuracy of the vehicle at the time of tracing. A vehicle control device (520) of the present invention includes an oversteer angle determination unit (508) that determines whether or not a steering angle of a vehicle (10) is an oversteer angle, a stationary steering determination unit (509) that determines whether or not stationary steering operation is performed on a vehicle, a route storage mode detection unit (505) that determines whether or not a route storage mode is set, a specific operation detection unit (507) that determines whether a steering angle is the oversteer angle or the stationary steering operation is performed in the route storage mode, and an output unit that outputs a control command of steering angle restriction control that restricts steering operation of a driver in the route storage mode in a case where the specific operation detection unit determines that a steering angle is the oversteer angle or the stationary steering operation is performed.

In at least some implementations, a method of estimating road friction, includes determining an actual steering load, determining a nominal steering load as a function of vehicle speed, steering angle, and a nominal road friction value, and comparing the actual steering load to the nominal steering load to determine an estimated road friction. In at least some implementations, the nominal steering load is not determined as a function of vehicle yaw, or vehicle lateral acceleration, or vehicle wheel speed compared to vehicle speed, or vehicle tire compliance or road wheel angle.

A method for detecting, a roadside object including, a three-dimensional object in the vicinity of a vehicle on a road surface includes recording at least one data set including a plurality of data points associated with a region in a lateral vicinity of the vehicle, the region at least partially including at least one wheel of the vehicle and the road surface, where each data point includes according, to whether it corresponds to the at least one wheel to the road surface or to the roadside object, determining a distance between a data point classified as corresponding to the at least one wheel and a data point classified as corresponding to the roadside object and generating a signal if the distance is below at least one threshold value.

In one embodiment, static-state curvature error compensation control logic for autonomous driving vehicles (ADV) receives planning and control data associated with the ADV, including a planned steering angle and a planned speed. A steering command is generated based on a current steering angle and the planned steering angle of the ADV. A throttle command is generated based on the planned speed in view of a current speed of the ADV. A curvature error is calculated based on a difference between the current steering angle and the planned steering angle. The steering command is issued to the ADV while withholding the throttle command, in response to determining that the curvature error is greater than a predetermined curvature threshold, such that the steering angle of the ADV is adjusted in view of the planned steering angle without acceleration.

Four-wheel steering of a vehicle, e.g., in which leading wheels and trailing wheels are steered independently of each other, can provide improved maneuverability and stability. A first vehicle model may be used to determine trajectories for execution by a vehicle equipped with four-wheel steering. A second vehicle model may be used to control the vehicle relative to the determined trajectories. For instance, the second vehicle model can determine leading wheels steering angles for steering leading wheels of the vehicle and trailing wheels steering angles for steering trailing wheels of the vehicle, independently of the leading wheels.

A power adjustment system and a power adjustment method of an autonomous mobile device are provided. In the power adjustment method, two first current control signals respectively transmitted to two drivers are outputted by a control module. A tilt angle of the autonomous mobile device is detected by an inertial measurement module. A travel route is planned by a navigation module, and the control module obtains a steering angle of the autonomous mobile device during a traveling process. According to different weight values of the autonomous mobile device stored in a database module, a weight of the autonomous mobile device is estimated by the control module. According to the two first current control signals and the weight, the steering angle, and the tilt angle of the autonomous mobile device, two second current control signals respectively transmitted to the two drivers are outputted by the control module.

Systems and methods for coordinating steering controls between towing vehicles and towed vehicles provide more cohesive parking experiences during towing events, including bidirectional charging towing events. The towed vehicle may be controlled to provide assistive parking steering maneuvers to assist the towing vehicle when parking during the towing event. The assistive parking steering maneuver may include maneuvering a drive wheel of the towed vehicle either toward or away from a detected curb or detected traffic, for example.

An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.

A vehicle control device includes a travel environment recognition device configured to recognize travel environment, a vehicle travel state detection device, and an autonomous/manual driving mode controller. The autonomous/manual driving mode controller includes a learning correction unit configured to store at least one of a plurality of control parameters indicating the vehicle travel state by operation of the driver in the autonomous driving mode, and to correct the control parameter in the autonomous driving mode according to the stored control parameter. When the stored control parameter is the control parameter changed by an operation by the driver midway in passing or after passing, the learning correction unit is configured to correct the control parameter in the autonomous driving mode so that an acceleration level or the deceleration level is increased midway in passing or after passing.