A computer-implemented method that, when executed by data processing hardware of a vehicle, causes the data processing hardware to perform operations is provided. The operations include gathering sensor data, calculating one or more groove detection confidence values with the sensor data using one or more groove detection modules, evaluating the one or more groove detection confidence values using a road groove detection fusion module, determining whether a road groove is detected, communicating road groove data to an advanced driver-assistance system, and adapting trajectory and steering controls of the vehicle.

A method for controlling a vehicle in a driving situation includes: determining a trajectory of the vehicle for the driving situation; determining a target steering angle on the basis of the trajectory; determining an actual steering angle of the vehicle in the driving situation; determining a steering angle deviation between the determined target steering angle and the determined actual steering angle; providing a steering angle tolerance value for the steering angle deviation; providing early detection of instability of the vehicle when the determined steering angle deviation violates the steering angle tolerance value; and in response to the early detection of instability of the vehicle: executing at least one driving dynamics intervention using at least one vehicle actuator of the vehicle to counteract the instability of the vehicle. A driver assistance system, a vehicle and a computer program product are configured to perform the method.

A method detects a yaw instability in a vehicle combination having a tractor unit and at least one trailing unit. The method includes determining a plurality of probability values each representing the probability of a yaw instability for the vehicle combination, wherein each probability value is based on a reference value and a current value of a respective parameter, applying a respective weight to each probability value, and determining a combined probability value representing the probability of a yaw instability occurring in the vehicle combination based on the weighted probability values.

A method for controlling in real time the path of a motor vehicle travelling in a traffic lane includes detecting a corner in the traffic lane, then, when the vehicle enters the corner, determining first and second quantities for a plurality of successive sampling increments, based on state variables characteristic of the movement of the vehicle, determining a first stored value dependent on the first quantity determined in the current sampling increment and one of the preceding sampling increments, determining a second stored value dependent on the second quantity determined in the current sampling increment and one of the preceding sampling increments, saving the first and second stored values determined for each sampling increment, then, when the vehicle exits the corner determining a value of the understeer gradient depending on the saved first and second stored values, and determining a command for the vehicle based on the understeer gradient.

Method comprising detecting that the vehicle is performing a transitional maneuver or detecting a braking request or a propulsion torque reduction while the vehicle is driving in a curve at grip limit based on first data indicative of driver intentions and/or vehicle motion state, detecting instability of the vehicle based on the first data, adjusting a torque request to the two clutches in response to the detected instability, wherein the two clutches are arranged to transmit the propulsion torque generated by the propulsion actuator to the wheels based on the torque request and based on the propulsion torque generated by the propulsion actuator, and wherein the torque request is adjusted based on the vehicle motion state and/or driver intentions such that a yaw motion of the vehicle is reduced.

A method of controlling a vehicle includes: receiving pieces of data related to steering of the vehicle; detecting, among the pieces of data, target pieces of data determined to satisfy predetermined conditions; based on the target pieces of data and an optimization model, obtaining optimized model parameters that minimize a cumulative error between a predicted yaw rate of a yaw rate model of the vehicle and a measured yaw rate of the vehicle; and updating the yaw rate model of the vehicle by using the optimized model parameters.