A method for off road driving, the method may include obtaining environment sensed information about an environment of a vehicle of a certain model, by one of more vehicle sensors of the vehicle and while driving over an off road path; detecting, by a machine learning process, an off road driving event; determining, by the machine learning process, a characteristic behavior of vehicles of the certain model when facing the off road driving event; and responding, at least in part by the machine learning process, to the occurrence of the off road driving event.

A slip control system for an off-road vehicle includes a control system configured to output a signal indicative of a first action if a magnitude of slippage of the off-road vehicle relative to a soil surface is greater than a first threshold value and less than or equal to a second threshold value. Furthermore, the control system is configured to output a signal indicative of a second action, different than the first action, if the magnitude of slippage is greater than the second threshold value.

A slip control system for an off-road vehicle includes a control system configured to output a signal indicative of a first action if a magnitude of slippage of the off-road vehicle relative to a soil surface is greater than a first threshold value and less than or equal to a second threshold value. Furthermore, the control system is configured to output a signal indicative of a second action, different than the first action, if the magnitude of slippage is greater than the second threshold value.

A tire device has a tire side device and a vehicle body side system, and determines a road surface condition and detects a tire wear state. The tire side device includes a vibration detection unit that outputs a detection signal according to a magnitude of a tire vibration, a control unit extracts a feature amount during one rotation of the tire, and a first data communication unit that transmits a road surface data including a feature amount. The vehicle body side system includes a second data communication unit that receives road surface data, a road surface determination part that determines a road surface condition based on the road surface data, an integral calculation part that calculates an integral value of the feature amount in a specific frequency band included in the road surface data, and a wear determination part that detects the tire wear state from the integral value.

An approach is provided for determining road surface friction data for at least one travel segment via sensor data and/or guideline friction map to cause at least one response action. The approach involves processing and/or facilitating a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment. The approach also involves causing, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map. The approach further involves determining at least one response action to the at least one road-vehicle friction change based, at least in part, on the comparison.

An approach is provided for determining road surface friction data for at least one travel segment via sensor data and/or guideline friction map to cause at least one response action. The approach involves processing and/or facilitating a processing of sensor data to determine at least one road-vehicle friction change associated with at least one travel segment. The approach also involves causing, at least in part, a comparison of the at least one road-vehicle friction change to at least one guideline friction map. The approach further involves determining at least one response action to the at least one road-vehicle friction change based, at least in part, on the comparison.

A road surface friction coefficient estimation apparatus for a vehicle includes: a first estimator; a second estimator; and a third estimator. The first estimator estimates a first road surface friction coefficient on a basis of a vehicle information acquired from the vehicle. The second estimator estimates a second road surface friction coefficient on a basis of an external information acquired from an outside of the vehicle. The third estimator estimates a road surface friction coefficient from the first road surface friction coefficient and the second road surface friction coefficient on a basis of a first reliability degree and a second reliability degree, the first reliability degree indicating a reliability of the first road surface friction coefficient, the second reliability degree indicating a reliability of the second road surface friction coefficient.

A road surface friction coefficient estimation apparatus for a vehicle includes: a first estimator; a second estimator; and a third estimator. The first estimator estimates a first road surface friction coefficient on a basis of a vehicle information acquired from the vehicle. The second estimator estimates a second road surface friction coefficient on a basis of an external information acquired from an outside of the vehicle. The third estimator estimates a road surface friction coefficient from the first road surface friction coefficient and the second road surface friction coefficient on a basis of a first reliability degree and a second reliability degree, the first reliability degree indicating a reliability of the first road surface friction coefficient, the second reliability degree indicating a reliability of the second road surface friction coefficient.

A method for predicting, for a motor vehicle traveling on a first road segment, a future coefficient of friction of the vehicle on a second road segment. The method includes steps of obtaining operating parameters of the vehicle and at least one characteristic of the first road segment, of computing an indicator on the basis of the obtained operating parameters of the vehicle, of determining a frictional category of the vehicle according to the value of the computed indicator and of the at least one obtained characteristic of the road segment, of selecting a friction profile of the vehicle on the basis of the determined frictional category, and of determining a coefficient of friction of the vehicle by applying the selected profile to at least one characteristic of the second road segment. A device for implementing the prediction method is also disclosed.

A method to control a road vehicle for the execution of a standing start; the control method comprises the steps of: engaging a gear in a transmission while a corresponding clutch is open; progressively closing the clutch causing the clutch to transmit a torque that causes the rotation of at least a pair of drive wheels; determining a target slip of the drive wheels; cyclically determining a real slip of the of the drive wheels; and continuously modulating the torque transmitted by the clutch during the closing of the clutch based of a difference between the target slip of the drive wheels and the real slip of the of the drive wheels.