An electronic parking brake system including: an electronic parking brake provided to generate a clamping force on a wheel of a vehicle; and a controller configured to estimate a weight of the vehicle based on a wheel pressure and a longitudinal acceleration of the vehicle at a time of service braking during driving, determine a clamping force required for parking based on the estimated weight of the vehicle during a parking operation, and operate the electronic parking brake to generate the determined clamping force.

A tire with a treads depth measuring device that includes a first electrode and a second electrode that are fixed to internal surface of the tire, and an oscillator that is electrically connected to the electrodes so that capacitance between the electrodes affects frequencies of the oscillator. Changes in frequencies of the oscillator can be used to detect and calculate changes in thickness of the tire and changes in depth of treads in the tire.

Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Method for estimating a brake factor parameter, the brake factor parameter being defined as a ratio of a braking torque over a braking pressure, the braking torque being applied on a wheel of a vehicle by a braking wheel sub-system of a braking system of the vehicle, the braking pressure being applied by the braking wheel sub-system to achieve the braking torque on the wheel of the vehicle, the method comprising collecting input parameters and estimating the brake factor parameter as a function of the at least one input parameter, an output of the step of estimating being an open loop estimation of the brake factor parameter.

In a road surface condition determining device, when determining a road surface condition, a vibration detection unit, a waveform processing unit and a data transmission unit for implementing a sensing function and a data transmission function are not set continuously to an active state for all tire side device, but at least only one tire side device is set to an active state. Remaining one or more is set to a sleep state. A reduction in power consumption of the tire side devices set to the sleep state can thus be achieved. Further, with regard to the at least one tire side device, since the sensing function and the data transmission function remain in the active state, the road surface condition can be reliably determined based on the road surface data of the tire side device.

Method for updating at least one vehicle model parameter and at least one tire parameter in at least one chassis control unit of a vehicle, based on tire sensor information collected by a tire sensor placed on a tire. The method includes the steps of: collecting tire sensor information; updating the at least one vehicle model parameter based on updating at least one tire parameter, updating one tire parameter being based on the tire sensor information.

Devices, systems, and methods related to prediction of tire performance using existing CAN data to improve overall vehicle performance. Machine learning tools are applied to CAN data, for example pilot data and/or vehicle dynamics data, to predict tire performance factors for use in a vehicle control system to provide vehicle lateral guidance control.

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.

Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Starting from an acceleration signal, representative of a radial acceleration undergone by a portion of a crown region of said tyre due to the rolling of said tyre on a rolling surface, the trend of the first derivative of the radial acceleration is determined at a portion representative of the interaction of the tyre with a water layer. From the trend of the first derivative of the radial acceleration, it is determined at least one first parameter representative of an aquaplane condition of the tyre on the basis of a comparison between a first maximum and a second maximum of the first derivative at the portion representative of the interaction between tyre and water layer.