The present disclosure relates to a method for determining the fatigue of a driver of a motor vehicle, wherein the fatigue is determined while taking into account the steering behavior of the driver, characterized in that the method includes the following steps: determination of a hysteresis of the steering system or the fatigue detection system, and taking into account the detected hysteresis in the determination of the fatigue of the driver. Furthermore, the disclosure relates to a device that is set up to execute the method.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

A lane centering system for use in a vehicle driving in a lane on a road includes a lane delimiter detection device having a camera with a field of view that encompasses the road ahead of the vehicle. Based on processing of captured image data, a controller determines the positions of left and right lane delimiters on the road. The controller is operable to establish a target path for the vehicle that maintains the longitudinal centerline of the vehicle generally centered between the left lane delimiter and the right lane delimiter. The controller is automatically activated to control steering the vehicle along the target path when the speed of the vehicle is at or above a first speed level. When having activated control of steering, the controller automatically deactivates control of steering when the speed of the vehicle falls to at or below a second speed level.

A lane centering system for use in a vehicle driving in a lane on a road includes a camera and a controller. Based on processing by a processor of image data captured by the camera, the controller determines position of a left lane delimiter on the road on a left side of the vehicle and position of a right lane delimiter on the road on a right side of the vehicle. The controller is operable to determine a target path for the vehicle based on processing of image data captured by the camera. The determined target path maintains the longitudinal centerline of the vehicle centered between the left lane delimiter and the right lane delimiter. The lane centering system may be enabled responsive to the vehicle speed exceeding a threshold speed, and may be disabled during a braking event of a collision mitigation system of the vehicle.

There is provided a method to stop or slow down a vehicle in an emergency, the method involving a vehicle comprising an emergency stop system which is able to cause the vehicle to stop or slow down, said emergency stop system comprising at least one microphone for detecting sounds in the vicinity of the vehicle, and a sound analysis unit for analysing sound, the method involving the steps: a) the microphone of the emergency stop system receiving a sound and sending a signal representing the sound to the sound analysis unit, b) the sound analysis unit of the emergency stop system determining that the received sound is a predetermined sound or a predetermined sound pattern, and c) the emergency stop system causing the vehicle to stop or slow down.

A vehicle control apparatus selects a control target object, based on object information and executes a collision avoidance control when a predetermined execution condition is satisfied. The vehicle control apparatus determines that a driver of an own vehicle carries out a first mistaken operation when a predetermined first pressing condition that the driver of the own vehicle strongly operates the acceleration operator, is satisfied, and a magnitude of the steering angle is greater than a predetermined first steering angle threshold, and permits executing the collision avoidance control when a first situation that the driver of the own vehicle carries out the first mistaken operation, and a distance between the own vehicle and the control target object is shorter than a predetermined first distance threshold, arises.

A computer includes a processor and a memory storing instructions executable by the processor to input steering torque data and steering wheel angle data to a machine learning program trained to output a status of a hand of an occupant relative to a steering wheel, the status being one of (1) the hand is on the steering wheel, (2) the hand is off the steering wheel and no weight is applied to the steering wheel, or (3) the hand is off the steering wheel and a weight is applied to the steering wheel, and actuate a steering subsystem when the output of the machine learning program indicates that the hand of the occupant is off the steering wheel.

Disclosed herein are a drowsy-driving prevention method and a drowsy-driving prevention system that execute artificial intelligence (AI) algorithms and/or machine learning algorithms in a 5G environment connected for Internet of Things in order to control a stimulation unit and a measurement unit. The drowsy-driving prevention method may include a stimulating step, a measuring step, and a determining step. A stimulation unit outputs a stimulus in order to stimulate a sensory organ of a driver, and then a measurement unit measures a biometric signal of the driver from the time when the stimulus is outputted. Upon determining that the biometric signal of the driver is not a response to the stimulus, the stimulation unit may output the stimulus again.

A traveling assistance apparatus controls a safety apparatus for avoiding collision between an own vehicle and an object, based on detection information from an object detection apparatus. The assistance apparatus calculates a predicted time to collision of a target object and the own vehicle, and operates the safety apparatus in response to the predicted time to collision being equal to or less than a predetermined operation timing. In response to a steering operation by a driver for collision avoidance of the own vehicle being performed, the assistance apparatus performs operation-stop in which operation of the safety apparatus is stopped or operation-delay in which the operation timing is delayed. The assistance apparatus suppresses the operation-stop or the operation-delay in response to a target object serving as a collision avoidance target being recognized in a path of the own vehicle after the steering operation by the driver, based on the detection information.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.