According to an embodiment, provided are a method and an apparatus for monitoring an unmanned ground vehicle (UGV), for detecting a failure of a UGV actuator in consideration of terrain information. Accordingly, the accuracy of detecting a failure of the UGV is improved.

According to an embodiment, provided are a method and an apparatus for monitoring an unmanned ground vehicle (UGV), for detecting a failure of a UGV actuator in consideration of terrain information. Accordingly, the accuracy of detecting a failure of the UGV is improved.

A method for determining a friction coefficient for a contact between a tire of a vehicle and a roadway. The method includes processing sensor signals in order to generate processed sensor signals. The sensor signals represent state data that are read in at least by at least one detection device and that are correlatable with the friction coefficient. The processed sensor signals represent at least one preliminary friction coefficient. The method also includes ascertaining the friction coefficient using the processed sensor signals and a regression model.

A method for determining a friction coefficient for a contact between a tire of a vehicle and a roadway. The method includes processing sensor signals in order to generate processed sensor signals. The sensor signals represent state data that are read in at least by at least one detection device and that are correlatable with the friction coefficient. The processed sensor signals represent at least one preliminary friction coefficient. The method also includes ascertaining the friction coefficient using the processed sensor signals and a regression model.

A road friction coefficient of a vehicle is estimated by obtaining substantially contemporaneous values associated with a steering angle for a steered axle of the vehicle, a lateral acceleration, a yaw acceleration, an alignment torque and an axle load on the steered axle; estimating a lateral tire force on the basis of the steering angle, lateral acceleration, and yaw acceleration; deriving a pneumatic trail from the alignment torque and estimated lateral tyre force; and estimating a road friction coefficient from the lateral tire force, the axle load, and the pneumatic trail. In embodiments, the derivation of the road friction coefficient includes evaluating a nonlinear function of the pneumatic trail.

A road friction coefficient of a vehicle is estimated by obtaining substantially contemporaneous values associated with a steering angle for a steered axle of the vehicle, a lateral acceleration, a yaw acceleration, an alignment torque and an axle load on the steered axle; estimating a lateral tire force on the basis of the steering angle, lateral acceleration, and yaw acceleration; deriving a pneumatic trail from the alignment torque and estimated lateral tyre force; and estimating a road friction coefficient from the lateral tire force, the axle load, and the pneumatic trail. In embodiments, the derivation of the road friction coefficient includes evaluating a nonlinear function of the pneumatic trail.

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.

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.

Provided is a control apparatus for a vehicle, the control apparatus being configured to determine a road surface μ state of a road in front of the vehicle based on an image of a front region of the vehicle, and change a magnitude of an amount of reduction in a braking force per unit time in accordance with the determined road surface μ state in braking force cancel control executed after hill-hold control

Provided is a control apparatus for a vehicle, the control apparatus being configured to determine a road surface μ state of a road in front of the vehicle based on an image of a front region of the vehicle, and change a magnitude of an amount of reduction in a braking force per unit time in accordance with the determined road surface μ state in braking force cancel control executed after hill-hold control