Disclosed are apparatuses and methods for controlling the steering of an autonomous vehicle. The apparatus including an electric power steering device to generate an assist torque for a steering wheel, an autonomous driving position controller to control a steering position according to a command steering angle input from an autonomous driving module, a driver steering intervention judger to judge whether a driver intervenes in steering based on a column torque and a vehicle speed, a weight detector to detect a weight for integrating output of an electric power steering device and output of an autonomous driving position controller based on judging whether the driver intervenes in steering, and an output controller to apply the weight to the output of the electric power steering device and the output of the autonomous driving position controller to integrate the output of the electric power steering device and the output of the autonomous driving position controller, wherein the autonomous driving position controller is further configured to adjust a gain value for controlling the steering position by applying the weight.

A computer includes a processor and a memory, the memory storing instructions executable by the processor to detect an actual steering column torque and an actual steering wheel angle, predict a steering wheel torque with a state-estimation algorithm that outputs a plurality of vehicle states including the predicted steering wheel torque, adjust the plurality of vehicle states based on an algorithm noise that is based on a steering wheel angular speed to generate estimated vehicle states, output the estimated vehicle states including an estimated user-applied steering wheel torque, and transition from an autonomous mode to a manual mode when the estimated steering wheel torque exceeds a threshold. The state-estimation algorithm accepts input including the actual steering column torque and the actual steering wheel angle and outputs the plurality of vehicle states.

An apparatus for controlling an MDPS system may include an MDPS-basic logic unit determining a first auxiliary command current for driving an MDPS motor in a manual driving mode, based on column torque applied to a steering column of a vehicle and a vehicle speed, an autonomous driving steering controller determining a second auxiliary command current for driving the MDPS motor in an autonomous driving mode, and a mode change controller determining a driver's steering intervention using a variable reference time variably determined based on the column torque in the manual driving mode, determining a mode change time from the autonomous driving mode to the manual driving mode based on the column torque, and determining a final auxiliary command current for driving the MDPS motor upon mode change, by applying, to the first and second auxiliary command currents, a weight into which the mode change time is incorporated.

A turning mechanism of a vehicle turns a wheel and is coupled to a steering wheel through a steering shaft. A torque sensor detects a torque applied to a first position of the steering shaft, as a sensor-detected torque. An upper friction torque is an absolute value of the sensor-detected torque that is caused by a friction force acting on the steering shaft between the first position and the steering wheel when the steering shaft is rotated. A vehicle control system repeatedly estimates the upper friction torque and variably sets a determination threshold to the estimated upper friction torque or more. The vehicle control system determines whether a driver state is a hands-on state or a hands-off state based on a comparison between the absolute value of the sensor-detected torque and the determination threshold.

A driving supporter includes a support inhibitor that inhibits support of driving when a steering-operation value is greater than a threshold value. The support inhibitor includes a threshold-value determiner that determines the threshold value to a value greater when a first object and a second object are present than when the first object is present, and the second object is absent. The first object has a relationship in which a relative positional relationship between the object and an own vehicle is a relationship in which a steering operation is estimated to be performed in a first direction in which the own vehicle avoids the object. The second object has a relationship in which the relative positional relationship is a relationship in which the steering operation is estimated to be performed in a second direction reverse to the first direction such that the own vehicle avoids the object.

A driving system for automated driving includes at least automated lateral guidance for a motor vehicle. The system is configured to determine whether one or more indications of a current or imminent manual steering intervention are present, which do not take place inadvertently and are intentional by a driver. Starting from a driving state with activated automated lateral guidance, the driving system deactivates the automated lateral guidance in response to the manual steering intervention. To deactivate the lateral guidance, a necessary steering torque operating counter to the activated lateral guidance is applied by the driver via the steering wheel within the scope of the manual steering intervention. When the at least one indication of the steering intervention intended by the driver is found to be present, the steering torque necessary to deactivate the lateral guidance is lower than when the indication of an intended steering intervention is not present.

Systems, methods, tangible non-transitory computer-readable media, and devices for operating an autonomous vehicle are provided. For example, the disclosed technology can include receiving state data that includes information associated with states of an autonomous vehicle and an environment external to the autonomous vehicle. Responsive to the state data satisfying vehicle stoppage criteria, vehicle stoppage conditions can be determined to have occurred. A severity level of the vehicle stoppage conditions can be selected from a plurality of available severity levels respectively associated with a plurality of different sets of constraints. A motion plan can be generated based on the state data. The motion plan can include information associated with locations for the autonomous vehicle to traverse at time intervals corresponding to the locations. Further, the locations can include a current location of the autonomous vehicle and a destination location at which the autonomous vehicle stops traveling.

A method for determining whether hands of an operator of a vehicle are positioned on a hand wheel of the vehicle is provided. The method generates a first frequency content below a first frequency from a hand wheel torque signal. The method generates a second frequency content above a second frequency from the first frequency content of the hand wheel torque signal. The method generates a hands on wheel (HOW) estimate signal based on the first frequency content and the second frequency content by determining a first contribution of the first frequency content to the HOW estimate signal, determining a second contribution of the second frequency content to the HOW estimate signal, and combining the first contribution and the second contribution to generate the HOW estimate signal. The method causes a system in a vehicle to operate based on the HOW estimate signal.

An electric power steering apparatus including a torque sensor to detect a steering torque and a motor control unit to control a motor that applies an assist torque to a steering system of a vehicle, including: a function to switch a control system of the motor between a torque control system to control a motor output torque and a position/speed control system to control a steering angle of a steering in accordance with a predetermined switching trigger. The fade processing time from the torque control system to the position/speed control system and the fade processing time from the position/speed control system to the torque control system are individually set.

A computer-implemented method, system, and/or computer program product controls a driving mode of a self-driving vehicle (SDV). One or more processors compare a control processor competence level of an on-board SDV control processor in controlling the SDV to a human driver competence level of a human driver in controlling the SDV while the SDV encounters a current roadway condition which is a result of current weather conditions of the roadway on which the SDV is currently traveling. One or more processors then selectively assign control of the SDV to the SDV control processor or to the human driver while the SDV encounters the current roadway condition based on which of the control processor competence level and the human driver competence level is relatively higher to one another.