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.

Disclosed is a system for preventing drunk driving of a vehicle, the system including: an input unit through which a transfer intention to transfer a control privilege of a vehicle from a registered driver to a passenger is input; a sobriety determination unit configured to determine a current driver's inebriation state through a breathalyzer provided in the vehicle when the transfer intention is input through the input unit; a driver verification unit configured to identify personal information of the current driver seated on a driver's seat; and a control unit configured to transfer the control privilege of the vehicle to the passenger when the passenger is measured as being able to drive by the sobriety determination unit and the passenger and the current driver are identified to be the same by the driver verification unit.

A computer-implemented method is described. The method is be implemented by processors of an aircraft system. The method includes receiving images of an eye and a lighting configuration associated with a cockpit of an aircraft. The method further includes detecting a position of the eye within each of the images. The method further includes compensating for a pupillary light response of the eye based on the position of the eye within the image and the lighting configuration. By compensating for the pupillary light response, a fatigue level of the operator is estimated with reduced noise.

A system and method for continuous real-time assessment of the situational awareness of an aircraft operator incorporates gaze sensors to determine the current gaze target (or sequence of gaze targets) of the operator, e.g., which interfaces the operator is looking at. The system receives operational context from aircraft systems indicative of current events and conditions both internal and external to the aircraft (e.g., operational status, mission or flight plan objectives, weather conditions). Based on the determined gaze targets and coterminous operational context, the system evaluates the situational awareness of the operator relative to the operational context, e.g., perceptive of the operational context; comprehending the operational context and its implications, and projecting the operator's perception and comprehension into responsive action and second-order ramifications according to task models indicative of expected behavior.

Disclosed are a drunk driving prevention system and a method of controlling the system that includes a sensor module measuring a alcohol content in the exhaled breath of a driver during a breath-checking of the driver and a control module configured to check the intoxication state of the driver from the alcohol content measured by the sensor module to determine whether the breath-checking is complete and block an engine start when the breath-checking fails, wherein the control module includes a check unit displaying breath-checking guide information through a display unit and the check unit displays the breath-checking guide information based on an engine start input of the driver.

Driver attention and hand placement systems and methods are disclosed herein. An example method includes providing warning messages to a driver of a vehicle based on steering wheel input or hand-wheel contact by the driver. The warning messages are provided according to a first scheme when the steering wheel input is above a threshold value and according to a second scheme when the steering wheel input is below a threshold value and images obtained by a camera in the vehicle indicate that at least one hand of the driver is on the steering wheel.

A system and method for inferring operator intent by detecting operator focus incorporates cameras positioned within a cockpit or control space of a vehicle and oriented at an operator of the vehicle. The cameras capture images of the operator in a control seat; the images are analyzed (either individually or sequentially) to determine a gaze and/or body pose of the operator (including, e.g., a position and orientation of the torso and limbs). By comparing the determined gaze and/or body pose to the positions and orientations of potential focus targets within the control space (e.g., windows, display units, and/or control panels that the operator may engage with visually and/or physically), the system predicts the most likely future focus target or targets: what the operator is most likely to visually and/or physically engage with next. Operator intent may be further analyzed to identify potentially abnormal or anomalous behavior.

A system for characterizing driver behavior includes an interface and a processor. The interface is configured to receive a set of vehicle data, wherein the set of vehicle data comprises embedded image vectors that characterize vehicle data over a short time scale. The processor is configured to determine, using a long time scale model, a long time scale label based at least in part on the embedded image vectors.

A device and a method are provided. The device includes a communication module, a memory, and a processor. The processor is configured to acquire position information of a vehicle via the communication module, determine whether high definition (HD) map information corresponding to the position information is acquired, display three-dimensional (3D) navigation information in augmented reality by using the HD map information when the HD map information is acquired, and display two-dimensional (2D) navigation information in augmented reality when the HD map information is not acquired. The 3D navigation information is information in which virtual 3D graphic information for driving guidance is spatially matched to and displayed on an actual object in the real world by using the HD map information, and the 2D navigation information is information in which virtual 2D graphic information for driving guidance is planarly matched to and displayed on an actual object in the real world.

A device may receive vehicle operation data associated with operation of a plurality of vehicles, and may process the vehicle operation data to generate processed vehicle operation data. The device may extract multiple features from the processed vehicle operation data, and may train machine learning models, with the multiple features, to generate trained machine learning models that provide model outputs. The device may process the multiple features, with a feature selection model and based on the model outputs, to select sets of features from the plurality of features, and may process the sets of features, with the trained machine learning models, to generate indications of driving behavior and reliabilities of the indications. The device may select a set of features, from the sets of features, based on the indications and the reliabilities, where the set of features may be calculated by a device associated with a particular vehicle.