An apparatus and method for predicting a friction coefficient of a road surface are disclosed. The apparatus includes a microphone that obtains a sound signal around a tire mounted on a vehicle, and a controller that estimates a state and a type of the road surface and a degree of tire wear corresponding to the sound signal around the tire based on a first deep learning model, estimates a peak adjustment factor and an initial inclination adjustment factor of a friction coefficient curve corresponding to the state and the type of the road surface and the degree of tire wear based on a second deep learning model, and predicts the friction coefficient based on the peak adjustment factor and the initial inclination adjustment factor of the friction coefficient curve.

A track for a track vehicle has sensor-receiving cavities disposed therein. Removeable sensors are placed in the sensor-receiving cavities for sensing characteristics of the track during operation.

A vehicle system includes an auxiliary vehicle that includes an auxiliary sensor and an auxiliary actuator, and a vehicle that communicates with the auxiliary vehicle. The vehicle includes an in-vehicle sensor that acquires information of an external environment of the vehicle, an in-vehicle actuator used in traveling of the vehicle, a vehicle control device that controls driving of the in-vehicle actuator using an input from the in-vehicle sensor, and a communicator that communicates with the auxiliary vehicle. The vehicle control device implement, upon detecting an abnormality in the in-vehicle sensor, one of the first switching control that controls the driving of the in-vehicle actuator based on an input from the auxiliary sensor, and a second switching control that causes the vehicle to travel using the auxiliary actuator.

An in-car safety system includes: a detecting device, a processor, an in-car equipment and a piezoelectric device. The detecting device is disposed on a car. The processor is disposed in the car. The processor is electrically connected to the detecting device. The processor is configured to receive a detecting signal transmitted by the detecting device and transmit an electrical signal in accordance with the detecting signal. The in-car equipment is disposed in the car. The piezoelectric device is disposed on the in-car equipment. The piezoelectric device is electrically connected to the processor. The piezoelectric device is configured to receive the electrical signal and generate a vibration to the in-car equipment in accordance with the electrical signal.

A method detects unintended acceleration of a motor vehicle during a closed-loop speed control mode by determining external forces on the vehicle via a controller, and then calculating a desired acceleration using a measured vehicle speed and the external forces. The method includes determining an actual acceleration of the vehicle, including filtering a speed signal as a first actual acceleration value and/or measuring a second actual acceleration value using an inertial measurement unit (IMU). During the speed control mode, the method includes calculating an acceleration delta value as a difference between the desired acceleration and the actual acceleration, and then using the acceleration delta value to detect the unintended acceleration during the speed control mode. A powertrain system for the motor vehicle, e.g., an electric vehicle, includes the controller and one or more torque generating devices coupled to road wheels of the vehicle.

A maximum friction coefficient estimation system includes a storage unit and a maximum friction coefficient calculation unit. The storage unit stores a table or a function for calculating a maximum friction coefficient between a tire and a road surface for a representative tire, based on a speed of rolling motion, load, temperature of the tire and a road surface condition level. The maximum friction coefficient calculation unit corrects the table or the function according to an individual tire specification and calculates the maximum friction coefficient.

A vehicular driving assist system includes a sensor disposed at a vehicle and operable to capture sensor data. An electronic control unit (ECU) includes electronic circuitry and associated software, and the electronic circuitry includes a data processor for processing sensor data captured by the sensor. The vehicular driving assist system, via processing at the data processor of sensor data captured by the sensor, detects a tread of a tire of the vehicle. The vehicular driving assist system determines a tread depth of the tread of the tire. The vehicular driving assist system, responsive to the determined tread depth being below a threshold tread depth, generates a worn tire signal to alert a driver of the vehicle that that the determined tread depth is below the threshold tread depth.

The present disclosure includes a system, method, and device related to data collection and communication related to after-market and external vehicle systems, such as towing systems, cargo carrying systems, trailer breakaway systems, brake systems, braking control systems, and the like. Data is sensed, processed, shared, and further leveraged throughout the discrete components of the system, and possibly via internet and other communications' links, to effect various beneficial actions with minimal driver/user interaction or intervention. In the same manner, data from the system may be used for diagnostic reasons, safety controls, and other purposes.

The disclosure relates to a method for monitoring behavior of a tire of a vehicle in a rolling condition of the tire, comprising the steps of: acquiring a signal representative of an acceleration of a specified point of the tire, deriving from the signal a curve which represents a profile of the acceleration of the point during a revolution of the tire, determining a leading portion and a trailing portion of the curve, corresponding to an entry of the point into a footprint region of the tire and corresponding to an exit of the point from the footprint region of the tire, respectively, determining a first measure of a volatility of the signal in the leading portion and a second measure of a volatility of the signal in the trailing portion, and determining an indication of the behavior of the tire based on the first measure and the second measure.

A method detects unintended acceleration of a motor vehicle during a closed-loop speed control mode by determining external forces on the vehicle via a controller, and then calculating a desired acceleration using a measured vehicle speed and the external forces. The method includes determining an actual acceleration of the vehicle, including filtering a speed signal as a first actual acceleration value and/or measuring a second actual acceleration value using an inertial measurement unit (IMU). During the speed control mode, the method includes calculating an acceleration delta value as a difference between the desired acceleration and the actual acceleration, and then using the acceleration delta value to detect the unintended acceleration during the speed control mode. A powertrain system for the motor vehicle, e.g., an electric vehicle, includes the controller and one or more torque generating devices coupled to road wheels of the vehicle.