A system and a method of improving a braking performance during a failure of a brake-by-wire (BBW) device, includes BBW devices including electro-mechanical brakes provided for respective wheels of a vehicle and independently performing braking, and the BBW devices including controllers electrically connected to the electro-mechanical brakes, and the system includes a steer-by-wire controller configured for controlling front wheels through an electronic signal and a rear wheel steering (RWS) controller configured for controlling steering of rear wheels such that a rear wheel steering angle is to be controlled in the same or an antiphase of a front wheel steering angle, wherein when one of the controllers fails, at least one of the steer-by-wire controller and the RWS controller is configured to control steering based on whether a driver's required braking force exceeds a maximum braking force which may be generated by any one of the front and rear wheels.

When there is an abnormality in communications between a motor ECU and an HVECU in an automobile, the motor ECU controls a motor such that creep torque or a given torque larger than the creep torque is delivered from the motor. Thus, when there is an abnormality in communications between the HVECU and the motor ECU, the automobile is able to run in a limp home mode.

Control system and method which is adapted for use in a motor vehicle and intended to effect an at least semi-autonomous driving operation of the motor vehicle by means of assigned actuators on the basis of environmental data which are obtained from one or more environment sensors assigned to the motor vehicle, and wherein the control system is adapted and intended to detect a failure of a conventional steering system of the motor vehicle and attempt a change of direction of the vehicle, which corresponds to a desired steering angle, from current driving parameters by means of matched acceleration and/or deceleration interventions at individual wheel drives or wheel brakes, respectively, of the vehicle.

The present disclosure relates to a method for controlling at least one drive assistance system of a motor vehicle, a device for carrying out the steps of this method and a system including such a device. The disclosure also relates to a motor vehicle including such a device or such a system.

A controller for a hybrid vehicle performs charging control when a shift range of the hybrid vehicle is a first range, and does not perform the charging control when the shift range of the hybrid vehicle is a second range, the charging control being control of charging a power storage device with electric power generated by a generator driven by an engine. The controller records diagnosis information when an SOC of the power storage device is equal to or lower than a first threshold value and the shift range of the hybrid vehicle is the first range, and does not record the diagnosis information when the SOC of the power storage device is equal to or lower than the first threshold value and the shift range of the hybrid vehicle is the second range.

Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. This may include receiving, by one or more processors of the vehicle, first information identifying a current relative humidity measurement within a sensor housing of a vehicle having an autonomous driving mode. The relative humidity measurement and pre-stored environmental map information may be used by the one or more processors to estimate a condition of a sensor within the sensor housing at a future time. This estimated condition may be used by the one or more processors to control the vehicle.

Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. This may include receiving, by one or more processors of the vehicle, first information identifying a current relative humidity measurement within a sensor housing of a vehicle having an autonomous driving mode. The relative humidity measurement and pre-stored environmental map information may be used by the one or more processors to estimate a condition of a sensor within the sensor housing at a future time. This estimated condition may be used by the one or more processors to control the vehicle.

A system for controlling an intelligent network vehicle is provided, and the system comprises a sensor group configured to obtain sensor information; a sensing and positioning module configured to obtain sensing information and positioning information based on the sensor information; a planning and control module configured to determine vehicle planning control information based on the sensing information and the positioning information; a safety control module configured to determine safety control information based on the sensing information and the positioning information; a function assessment module configured to determine a vehicle state assessment result; a risk assessment module configured to determine a risk assessment result; a logical arbitration module configured to determine vehicle execution information by arbitrating the vehicle planning control information and the safety control information; and an execution module configured to control the vehicle driving based on the vehicle execution information.

A method for controlling autonomous driving in a vehicle capable of the autonomous driving may include collecting vehicle travel status information and system status information during the autonomous driving, sensing a failure based on the system status information, identifying normally controllable actuators when sensing the failure, determining a risk degree corresponding to the sensed failure based on the normally controllable actuator information and the vehicle travel status information, determining a safety state based on normally controllable actuator information and the risk degree, and determining a failure safety strategy corresponding to the safety state.

A method for controlling autonomous driving in a vehicle capable of the autonomous driving may include collecting vehicle travel status information and system status information during the autonomous driving, sensing a failure based on the system status information, identifying normally controllable actuators when sensing the failure, determining a risk degree corresponding to the sensed failure based on the normally controllable actuator information and the vehicle travel status information, determining a safety state based on normally controllable actuator information and the risk degree, and determining a failure safety strategy corresponding to the safety state.