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.

According to one embodiment, a method, computer system, and computer program product for using mobile devices for anomaly detection in a vehicle. The present invention may include a computer receives sensor data from at least one mobile device associated with the vehicle, where the mobile device having one or more sensors. The computer analyzes data from the one or more sensors to identify an anomaly associated with the vehicle. The computer identifies a message associated with the anomaly. The computer determines an urgency value of the message based on the anomaly. The computer transfers the message with the urgency value to the vehicle and causes the vehicle to notify the message using a vehicle notification device.

A method for controlling corrected target hydraulic brake force to be generated by estimating friction coefficient variation depending on a bushing degree of a brake friction material and a season change, may include: determining a hydraulic brake torque required for hydraulic braking according to a driver's request brake torque; converting the hydraulic brake torque into a brake hydraulic pressure by use of a torque factor which is a friction capability of a brake friction material in the hydraulic brake torque; and determining a correction amount of the torque factor according to a season and a bushing degree of the brake friction material, which influences a friction coefficient which is an element of the torque factor.

A method for controlling corrected target hydraulic brake force to be generated by estimating friction coefficient variation depending on a bushing degree of a brake friction material and a season change, may include: determining a hydraulic brake torque required for hydraulic braking according to a driver's request brake torque; converting the hydraulic brake torque into a brake hydraulic pressure by use of a torque factor which is a friction capability of a brake friction material in the hydraulic brake torque; and determining a correction amount of the torque factor according to a season and a bushing degree of the brake friction material, which influences a friction coefficient which is an element of the torque factor.

A system of modeling an anti-lock brake system (ABS) controller of a vehicle includes: a vehicle speed estimation network configured to estimate a vehicle speed through machine learning using wheel speed data of each of a plurality of wheels of the vehicle; a wheel speed state estimation network configured to estimate a time series characteristic of the wheel speed through machine learning using information on the wheel speed data and information on whether a brake pedal is depressed; and a classification network configured to estimate a braking mode for controlling an increase, a decrease, or steady state of a braking pressure of each wheel through machine learning using speed estimation data of the vehicle estimated by the vehicle speed estimation network and time series characteristic estimation data of the wheel speed estimated by the wheel speed state estimation network.

A system of modeling an anti-lock brake system (ABS) controller of a vehicle includes: a vehicle speed estimation network configured to estimate a vehicle speed through machine learning using wheel speed data of each of a plurality of wheels of the vehicle; a wheel speed state estimation network configured to estimate a time series characteristic of the wheel speed through machine learning using information on the wheel speed data and information on whether a brake pedal is depressed; and a classification network configured to estimate a braking mode for controlling an increase, a decrease, or steady state of a braking pressure of each wheel through machine learning using speed estimation data of the vehicle estimated by the vehicle speed estimation network and time series characteristic estimation data of the wheel speed estimated by the wheel speed state estimation network.

A braking system including a brake actuator, a control valve, a control assembly, and at least one pressure sensor. The control valve is disposed to direct hydraulic fluid to the brake actuator at a rate corresponding to a magnitude of a control signal. The control assembly includes a mixed-mode control system. The at least one pressure sensor is configured to measure a pressure of the hydraulic fluid to the brake actuator. The control assembly is configured to determine a position of the brake actuator. The mixed-mode control system is configured to determine a position command and a pressure command. The mixed-mode control system is configured to adjust the magnitude of the control signal based on at least one of the position command and the pressure command so as to reposition the brake actuator from a first position to a second position.

A braking system including a brake actuator, a control valve, a control assembly, and at least one pressure sensor. The control valve is disposed to direct hydraulic fluid to the brake actuator at a rate corresponding to a magnitude of a control signal. The control assembly includes a mixed-mode control system. The at least one pressure sensor is configured to measure a pressure of the hydraulic fluid to the brake actuator. The control assembly is configured to determine a position of the brake actuator. The mixed-mode control system is configured to determine a position command and a pressure command. The mixed-mode control system is configured to adjust the magnitude of the control signal based on at least one of the position command and the pressure command so as to reposition the brake actuator from a first position to a second position.

A driving assistance apparatus is configured to provide deceleration assistance of decelerating a host vehicle, and is configured to end the deceleration assistance on condition that a pedal operation is performed by a driver while the deceleration assistance is provided. The driving assistance apparatus is provided with: an estimator configured to estimate an operation intention of the driver associated with an operation of a brake pedal, on condition that the brake pedal is operated by the driver while the deceleration assistance is provided; and a controller programmed to delay timing in which a deceleration assistance amount associated with the deceleration assistance becomes zero at the end of the deceleration assistance, if the estimated operation intention is caused by the target, in comparison with that if the estimated operation intention is not caused by the target.

A driving assistance apparatus is configured to provide deceleration assistance of decelerating a host vehicle, and is configured to end the deceleration assistance on condition that a pedal operation is performed by a driver while the deceleration assistance is provided. The driving assistance apparatus is provided with: an estimator configured to estimate an operation intention of the driver associated with an operation of a brake pedal, on condition that the brake pedal is operated by the driver while the deceleration assistance is provided; and a controller programmed to delay timing in which a deceleration assistance amount associated with the deceleration assistance becomes zero at the end of the deceleration assistance, if the estimated operation intention is caused by the target, in comparison with that if the estimated operation intention is not caused by the target.