A driver assistance method and a driver assistance apparatus are provided, which may be applied to the field of autonomous driving or intelligent driving. The driver assistance method includes: determining that a driver is in an abnormal state; determining that a first operation performed by the driver on a first terminal is an abnormal operation; and performing first processing, where the first processing includes outputting indication information and/or control information, and the indication information or the control information indicates a second operation performed on the first terminal, or the first processing includes controlling the first terminal to perform the second operation.

According to the present disclosure, a drunk driving prevention system including: an alcohol detection unit configured to detect a driver's inebriation through the breath test device provided in a vehicle; a computation unit configured, when the driver is detected to be in a drunk state by the alcohol detection unit, to compute a driving-possible time at which the drunk state is resolved in the future so that driving is possible; and a notification unit configured to output the driving-possible time or whether or not driving is possible through an infotainment system of the vehicle or a driver's terminal is disclosed.

In one embodiment, a cognitive load driving assistant increases driving safety based on cognitive loads. In operation, the cognitive load driving assistant computes a current cognitive load of a driver based on sensor data. If the current cognitive load exceeds a threshold cognitive load, then the cognitive load driving assistant modifies the driving environment to reduce the cognitive load required to perform the primary driving task and/secondary task(s), such as texting via a cellular phone. The cognitive load driving assistant may modify the driving environment indirectly via sensory feedback to the driver or directly through reducing the complexity of the primary driving task and/or secondary tasks. In particular, if the driver is exhibiting elevated cognitive loads typically associated with distracted driving, then the cognitive load driving assistant modifies the driving environment to allow the driver to devote appropriate mental resources to the primary driving task, thereby increasing driving safety.

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.

An awakening degree detecting device outputs awakening degree information corresponding to an awakening degree of a driver of a vehicle. A stimulus providing device provides the driver with a stimulus including at least one of a vibration stimulus imparting vibration and an apparent motion stimulus giving an illusion of motion presence. A control device outputs, based on the awakening degree information, a first control signal causing the stimulus providing device to provide the stimulus in a case where the awakening degree is less than a first threshold, and to output a second control signal causing the stimulus providing device to provide the stimulus after the first control signal is outputted.

A method for signaling a measured and/or a predetermined vital parameter and/or vital parameter pattern for a vehicle occupant in a vehicle involves arranging a functional element set up to have a visual and/or audible and/or haptic effect on at least one vehicle occupant, and a measured and/or a predetermined vital parameter and/or vital parameter pattern is signaled non-verbally by the functional element.

Disclosed are a drinking under influence (DUI) detection system and a DUI detection method based on an MQ3 sensor and an ultra wide band (UWB) radar. The system includes an alcohol detection module, a respiratory detection module, a signal matching module and a drunk driving alarm module, and each module cooperates to complete a detection. The MQ3 sensor-based alcohol detection module is used for alcohol signal capture, alcohol sequence processing and DUI threshold detection; the UWB radar-based respiratory detection module is used for respiratory signal capture, respiratory signal processing and passenger separation and positioning; the signal matching module is used for periodic signal alignment, sequence feature matching and drinker identity confirmation; and the DUI alarm module is used for a system alarm prompt, a data visualization interface and a DUI information uploading.

An arousal support device including a processor programmed to output a dialogue speech in a form of a question, and obtain response speech which is a response of a driver to the dialogue speech; measure a response time from when the dialogue speech is output till the response speech is obtained; store the measured response time in a database; derive an estimated value of wakefulness of the driver based on the measured response time and a plurality of response times previously stored in the database; and output a signal corresponding to the estimated value to provide arousal support.

A vehicle control apparatus operates in various modes, e.g., a normal mode in which plural travel functions of a vehicle are controlled by plural driving functions of a driver; an automatic mode in which all driving functions are performed by the vehicle; an optimization mode in which, when a temporary reduction of driving performance of any of the plural driving functions of the driver is detected, physical stimulation and/or information that makes the driver recognize the temporary reduction of the driving performance is provided to the driver; and an assistance mode in which, when a chronic reduction of the driving performance of any of the plural driving functions of the driver is detected, information on assistance with execution of the driving performance is provided to the driver.

Disclosed is a simulation learning-based drowsy driving simulation platform system for detecting careless driving in conjunction with deep learning, the simulation learning-based drowsy driving simulation platform system comprising: a drive state warning device configured to determine a driver's careless driving from a captured image, determine a driver's careless driving determination level, and output the determined level; a smart cruise control interworking part configured to transmit the driver's careless driving determination level outputted from the drive state warning device; and a smart cruise control processing part configured to control a vehicle according to the driver's careless driving determination level transmitted by the smart cruise control interworking part, during a smart cruise control operation.