A method for determining a tread depth of a tread of a tire during operation of a vehicle having the tire, a control device for a vehicle for determining a tread depth of a tread of a tire of the vehicle, and a system for a vehicle having such a control device and at least one electronic wheel unit, are provided. Provision is made to determine the tread depth based on a determined instantaneous dynamic wheel radius of a wheel, having the tire, of the vehicle and a determined instantaneous dynamic inside radius of the tire. In addition, at least one further first operating parameter of the tire, selected from the group including an instantaneous roadway gradient, an instantaneous vehicle drive mode and an instantaneous tire material expansion, is determined and taken into consideration.

A method includes an initial trailer health assessment and real-time trailer health monitoring. The initial trailer health assessment includes autonomous pre-trip maneuvers of the autonomous vehicle during a first time period, and detecting a pre-trip vehicle health condition. A vehicle health score is calculated based on the pre-trip vehicle health condition. If the vehicle health score is at least a threshold value, real-time trailer health monitoring is performed during a trip of the autonomous vehicle during a second time period, by actively monitoring vehicle dynamics data and/or image data associated with the autonomous vehicle, to determine a fault condition of the autonomous vehicle. If the fault condition meets a first criteria, a control parameter and/or a travel plan of the autonomous vehicle is adjusted. If the fault condition meets a second criteria different from the first criteria, a signal is sent to cause the autonomous vehicle to cease movement.

A computer implemented method for controlling at least one driven and/or braked wheel of a heavy-duty vehicle. The method includes obtaining a motion request indicative of a desired longitudinal acceleration and/or longitudinal force associated with the vehicle, and configuring a wheel slip limit value indicative of a maximum allowable wheel slip by the at least one driven and/or braked wheel at a nominal value, and increasing the wheel slip limit value from the nominal value to a boost wheel slip value in response to detecting a boost signal, as well as controlling the at least one driven and/or braked wheel in dependence of the motion request and subject to the wheel slip limit value.

A method for estimating a friction between a road surface and a tire of a steered wheel of a vehicle. The steered wheel being fit with dynamic steering. The vehicle includes a steering wheel and a set of sensors comprising wheel end sensors and steering wheel sensors configured to measure signals corresponding to a set of parameters., The steering wheel parameters comprising at least a steering wheel torque and a steering wheel angle. The method comprising the following steps implemented by the electronic control unit collect the signals, corresponding to the set of parameters, measured by the sensors during a period of time; process, by the signal processing module, the signals collected to provide processed signal data provide the processed signal data as input to the wheel end friction estimation model, the wheel end friction estimation model being configured to output a friction estimation of the friction between the road surface and the tire of the wheel.

A computer-implemented method performed in a vehicle control unit for controlling motion of a heavy-duty vehicle. The method includes obtaining a vehicle motion request, wherein the vehicle motion request is indicative of a target curvature and a target acceleration, determining a motion support device, MSD, control allocation based on the vehicle motion request, determining a dynamic wheel slip angle limit based on the vehicle motion request, where dynamic wheel slip angle limit increases with a decreasing target acceleration, and controlling the motion of the heavy-duty vehicle based on the MSD control allocation constrained by the dynamic wheel slip angle limit.

A driving lane keeping control system includes a number of vehicles and a server. Each vehicle is configured to transmit wheel position information to the server. The server is configured to receive the wheel position information from each vehicle, to match the wheel position information with a detailed map to generate a moving trajectory of each vehicle, to analyze the generated moving trajectory of each vehicle to select an optimum moving trajectory, to generate virtual lane information based on the selected optimum moving trajectory, and to transmit the generated virtual lane information to at least one of the vehicles to enable the at least one vehicle to correct a driving position based on the virtual lane information.

A vehicle information processing method for calculating a feature related to an operation of a vehicle includes: receiving input information including at least one of information on a driving operation performed on the vehicle, information on an operating state of driver assistance of the vehicle, and information on a behavior of the vehicle; and calculating the feature by using the input information received during a predetermined period in which a predetermined condition is satisfied out of a period in which the input information is received. The predetermined condition includes a condition that a driving situation of the vehicle is a predetermined driving situation corresponding to the feature.

Embodiments of the present disclosure disclose a method for controlling an autonomous vehicle to pass through a curve, a device and a medium, and relate to the field of autonomous driving technologies. At least one implementation of the method for controlling an autonomous vehicle to pass through a curve includes: determining a curve boundary within a sensing area in a current driving direction of the autonomous vehicle based on a current position of the autonomous vehicle on the curve; determining a current safe stopping distance of the autonomous vehicle on the curve based on current driving parameters of the autonomous vehicle and the curve boundary; determining a speed threshold of the autonomous vehicle based on the current safe stopping distance, braking parameters of the autonomous vehicle and a curve curvature corresponding to the current position; and controlling a speed of the autonomous vehicle not to exceed the speed threshold.

Terrain characteristics of an off-road area are determined based on a map. The terrain characteristics include a terrain type, a terrain grade, and a presence or an absence of an obstacle. Vehicle characteristics are determined including a ground clearance and a breakover angle. Based on a user level, vehicle parameters for the off-road area are determined based on the terrain characteristics, the vehicle characteristics, and the user input. The vehicle parameters include a speed and a transmission gear. The vehicle parameters for the off-road area are output.

A vehicle control apparatus configured to calculate a center of gravity six-component; calculate a tire three-component of each wheel for two or more wheels of a vehicle imposing a constraint on each wheel expressed as an inequality corresponding to upper and lower limits of the tire three-component; apply the constraint based on whether the constraint is valid or invalid for each of the wheels based on a predetermined optimum-condition for obtaining an optimum-solution under the constraint, and calculating an optimum-solution of the tire three-component of each wheel by performing a tentative-optimum-solution-calculation one or more times until the predetermined optimum-condition is satisfied; and store an application-state of the constraint when the optimum-solution satisfying the predetermined optimum-condition is obtained, and calculate the optimum-solution of the tire three-component of each wheel by using a stored value of the application-state of the constraint, in the next calculation of the optimum-solution.