A method for processing friction data for vehicle tires on road segments, implemented by a processing system including at least one computer and an interface for remote communication with a plurality of vehicles, the method including: acquiring, from the plurality of vehicles, friction data for tires of the vehicles on a plurality of road segments, each friction datum including at least: a maximum coefficient of friction available to the vehicle on the road segment, and information relating to the road segment; establishing, for each road segment, a distribution of the friction data obtained from the plurality of vehicles for the road segment; and determining a plurality of road types, each road type comprising a set of road segments, from a measurement of similarity between the distributions of friction data obtained for each road segment.

A method for processing friction data for vehicle tires on road segments, implemented by a processing system including at least one computer and an interface for remote communication with a plurality of vehicles, the method including: acquiring, from the plurality of vehicles, friction data for tires of the vehicles on a plurality of road segments, each friction datum including at least: a maximum coefficient of friction available to the vehicle on the road segment, and information relating to the road segment; establishing, for each road segment, a distribution of the friction data obtained from the plurality of vehicles for the road segment; and determining a plurality of road types, each road type comprising a set of road segments, from a measurement of similarity between the distributions of friction data obtained for each road segment.

A vehicle control device configured to control switching of drive mode of a vehicle including an internal combustion engine and a motor includes a processor configured to switch, in a case where a road surface of a perimeter of a geofencing zone is a road surface on which there is a high probability that the vehicle slips, in a movement route from an outside of the geofencing zone to an inside of the geofencing zone, the drive mode of the vehicle to drive by the motor in a state in which there is a low probability that the vehicle slips, outside the geofencing zone.

A vehicle control device configured to control switching of drive mode of a vehicle including an internal combustion engine and a motor includes a processor configured to switch, in a case where a road surface of a perimeter of a geofencing zone is a road surface on which there is a high probability that the vehicle slips, in a movement route from an outside of the geofencing zone to an inside of the geofencing zone, the drive mode of the vehicle to drive by the motor in a state in which there is a low probability that the vehicle slips, outside the geofencing zone.

According to one or more embodiments, a method includes computing, by a steering system, a model rack force value based on a vehicle speed, steering angle, and a road-friction coefficient value. The method further includes determining, by the steering system, a difference between the model rack force value and a load rack force value. The method further includes updating, by the steering system, the road-friction coefficient value using the difference that is determined.

According to one or more embodiments, a method includes computing, by a steering system, a model rack force value based on a vehicle speed, steering angle, and a road-friction coefficient value. The method further includes determining, by the steering system, a difference between the model rack force value and a load rack force value. The method further includes updating, by the steering system, the road-friction coefficient value using the difference that is determined.

A method for determining road surface conditions in a system with at least one vehicle and a data processing device. The vehicle exchanges data with the data processing device wirelessly. The vehicle has at least one sensor for determining measured values describing a road surface friction coefficient, and a computing unit. The data processing device includes a database, containing a road map having a plurality of route sections. The method includes determining measured values for a route section by the sensor, determining a first friction coefficient for the route section by the vehicle's computing unit, sending a data record, containing measured values and/or the first determined friction coefficient and a piece of information identifying the route section, to the data processing device, determining an average friction coefficient for the route section, sending the average friction coefficient determined for the route section to the vehicle, and determining the road surface condition.

A control apparatus for a vehicle includes: a target yaw rate calculator; a primary limit yaw rate calculator; a yaw rate comparator; a secondary limit yaw rate calculator; and a vertical load controller. The target yaw rate calculator calculates a target yaw rate of the vehicle. The primary limit yaw rate calculator calculates a primary limit yaw rate on a basis of a vertical load on a wheel. The yaw rate comparator compares the target yaw rate with the primary limit yaw rate. The secondary limit yaw rate calculator calculates a secondary limit yaw rate in a case where a distribution of the vertical load on the wheel is changed in a case where the target yaw rate exceeds the primary limit yaw rate. The vertical load controller changes the vertical load on a basis of the secondary limit yaw rate.

A control apparatus for a vehicle includes: a target yaw rate calculator; a primary limit yaw rate calculator; a yaw rate comparator; a secondary limit yaw rate calculator; and a vertical load controller. The target yaw rate calculator calculates a target yaw rate of the vehicle. The primary limit yaw rate calculator calculates a primary limit yaw rate on a basis of a vertical load on a wheel. The yaw rate comparator compares the target yaw rate with the primary limit yaw rate. The secondary limit yaw rate calculator calculates a secondary limit yaw rate in a case where a distribution of the vertical load on the wheel is changed in a case where the target yaw rate exceeds the primary limit yaw rate. The vertical load controller changes the vertical load on a basis of the secondary limit yaw rate.

A road surface state estimation device includes a tire-side device and a vehicle-body-side system. The tire-side device is disposed in a tire. The vehicle-body-side system is disposed in a vehicle body. The tire-side device outputs a detection signal corresponding to a magnitude of vibration of the tire, generates road surface data based on the detection signal, and performs data communication with the vehicle-body-side system. The vehicle-body-side system acquires information related to the road surface state, performs the data communication with the tire-side device, transmits vehicle-body-side information indicating that the change in the road surface state occurs to the tire-side device when determining that a change in the road surface state occurs based on the information related to the road surface state, and estimates the road surface state based on the road surface data received by the second transceiver.