Processing to estimate a type of a road surface is executed repeatedly. In the m-th processing, a holding time of an estimation result obtained by the m-th processing is set based on gradient data just before the m-th processing. The holding time is set to a longer duration as an uplink gradient of the road surface indicated by the latest gradient data increases. In the (m+n)-th processing, it is determined whether or not a feature portion is recognized from an imaging data. If this determination result is negative, the holding time is compared with a UNDEF period during which it has been determined that no feature portion has been recognized backward from the (m+n)-th processing. If the holding time is longer than the UNDEF period, then the estimation result obtained in the (m+n)-th processing is assumed to be the same as that obtained in the m-th processing.

A control unit (130, 140, 300) for controlling a heavy duty vehicle (100), wherein the control unit is arranged to obtain an acceleration profile (a.sub.req) and a curvature profile (c.sub.req) indicative of a desired maneuver by the vehicle (100), the control unit (130, 140, 300) comprising a force generation module (310) configured to determine a set of global vehicle forces and moments required to execute the desired maneuver, the control unit (130, 140, 300) further comprising a motion support device, MSD, coordination module (320) arranged to coordinate one or more MSDs to collectively provide the global vehicle forces and moments by generating one or more respective wheel forces, and an inverse tyre model (330) configured to map the one or more wheel forces into equivalent wheel slips (λ), wherein the control unit (130, 140, 300) is arranged to request the wheel slips (λ) from the MSDs.

An illustrative example method is for estimating a friction characteristic of a surface beneath a vehicle that has a plurality of wheels contacting the surface. The method includes determining a wheel speed of at least one of the wheels, determining a velocity of the at least one of the wheels separately from determining the wheel speed, determining a wheel slip of the at least one of the wheels based on the determined wheel speed and the determined velocity, and determining the friction characteristic based on the determined wheel slip. Determining the velocity separately from the wheel speed is accomplished using at least one detector that provides an output corresponding to a range rate, such as a RADAR or LIDAR detector.

A method for assessing contamination of a rail, in particular for a railway vehicle, comprises the steps of imposing a first sliding value lower than a first threshold between the wheels of a first controlled axle and the rail, the first controlled axle being the head axle of the railway vehicle, imposing a second sliding value greater than a second threshold between the wheels of a second controlled axle and the rail, the second axle following the first axle and the second threshold being greater than the first threshold, and determining the trend of an adhesion curve between the wheels belonging to a plurality of controlled axles and the rail, based on a first adhesion value between the wheels of the first axle and the rail, and a second adhesion value between the wheels of the second axle and the rail.

The present invention relates to a method and device for estimating the road surface friction coefficient of a tire, which estimate the road surface friction coefficient of a tire mounted on a wheel of a vehicle in a state in which the vehicle is normally running at high speed. The method includes: acquiring the state information of a vehicle including at least one of engine state information, transmission state information, and chassis state information from sensors mounted on the vehicle and specifications set for the vehicle; estimating a longitudinal slip ratio, normal force, and longitudinal force for a tire mounted on each wheel of the vehicle by using the acquired state information of the vehicle; and estimating a road surface friction coefficient for the tire by using the estimated longitudinal slip ratio, normal force, and longitudinal force.

The present disclosure relates to a method for autonomously controlling a vehicle performed by a vehicle control system, the vehicle control system comprising a zone control system, a collision prediction system and a braking control system, the method comprising the steps of: defining in the zone control system at least a first zone and a second zone relative to a vehicle position, predicting a collision with an obstacle with the prediction system, autonomously braking the vehicle with the braking control system in a first braking mode if the collision is predicted to occur in the first zone and braking the vehicle with the braking control system in a second braking mode if the collision is predicted to occur in the second zone.

A driving assistance apparatus includes a processor having hardware. The processor is configured to acquire vehicle speed data before an ABS of a vehicle is activated and vehicle speed data when the ABS of the vehicle is stopped, calculate a coefficient of sliding friction based on the vehicle speed data before the ABS is activated and the vehicle speed data when the ABS is stopped, determine whether the coefficient of sliding friction is equal to or smaller than a threshold, and detect that a slip due to road freezing has occurred when the coefficient of sliding friction is equal to or smaller than the threshold.

A braking control system and method for a vehicle are configured to calculate a braking force of front and rear wheels using a wheel slip ratio of the front and rear wheels and a road surface friction coefficient and then accurately estimate and calculate a disk temperature of the front and rear wheels using a predetermined estimation formula from the calculated braking force, and control distribution of braking pressure to the front wheels and the rear wheels so as to uniformly wear brake pads based on the calculated temperatures of the disks.

A stability control system of a vehicle utilizing an electronic control unit that detects a yaw condition while each of the wheel brakes are actuated by EBCM and the wheel speeds are zero. An electronic control unit includes an electronic braking control module that controls actuation and de-actuation of vehicle brakes on an inclined surface. A yaw condition is identified while all vehicle brakes are actuated on the inclined surface and each wheel speed is zero. The electronic control unit identifies which uphill wheel is leading a direction of the yaw and identifies a wheel of an opposing axle diagonal to the identified uphill wheel. The electronic control unit in cooperation with the electronic braking control module de-actuates the vehicle brakes of the identified uphill wheel and diagonal wheel to increase a side friction to the identified diagonal wheels to reduce further yawing of the vehicle.

A braking control system includes braking control modules configured to generate a braking torque request signal, indicative of a requested braking torque value CFr, which is variable until reaching a target value Vt, and to supply the braking torque request signal to a braking means which converts it into a braking torque with effective braking torque value CFe. The braking control modules are configured to calculate a total difference of instantaneous braking torque ΔCFt as the sum of the differences between the CFr values and the CFe values of all modules. If the calculated ΔCFt is greater than zero when Vt is reached, the braking control modules increase the braking torque until a ΔCFt subsequent to reaching Vt has a zero or negative value, or until the maximum available adhesion signal has indicated that a controlled axle has reached the maximum available adhesion.