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.

A vehicle includes a processing device that detects an authentication device approaching the vehicle, determines a user's impaired state based on user condition information acquired using at least one device mounted on the vehicle, and performs a safe driving assistance service. The safe driving assistance service can prevent an impaired user from operating the vehicle.

The described systems and methods determine a driver's fitness to safely operate a moving vehicle based at least in part upon observed UVB exposure patterns, where the driver's UVB exposure levels may serve as a proxy for vitamin D levels in that driver's body. A smart ring, wearable on a user's finger, continuously monitors user's exposure to UVB light. This UVB exposure data, representing UVB exposure patterns, can be utilized, in combination with driving data, to train a machine learning model, which will predict the user's level of risk exposure based at least in part upon observed UVB exposure patterns. The user can be warned of this risk to prevent them from driving or to encourage them to get more sunlight exposure before driving. In some instances, the disclosed smart ring system may interact with the user's vehicle to prevent it from starting while exposed to high risk due to deteriorated psychological or physiological conditions stemming from insufficient UVB exposure.

The described systems and methods determine a driver's fitness to safely operate a moving vehicle based at least in part upon observed impairment patterns. A smart ring, wearable on a user's finger, continuously monitors impairment levels. This impairment data, representing impairment patterns, can be utilized, in combination with driving data, to train a machine learning model, which will predict the user's level of risk exposure based at least in part upon observed impairment patterns. The user can be warned of this risk to prevent them from driving or to encourage them to delay driving. In some instances, the disclosed smart ring system may interact with the user's vehicle to prevent it from starting while the user is in a state of impairment induced by substance intoxication.

A system includes: a first camera configured to capture first images of a driver on a driver's seat within a passenger cabin of a vehicle; a second camera configured to capture second images in front of the vehicle; a driver module configured to determine a driver of the vehicle based on at least one of the first images and to determine a present driver's licensing level of the driver with a driver's licensing body; a first detection module configured to detect first occurrences of first conditions within the passenger cabin of the vehicle based on the first images; a second detection module configured to detect second occurrences of second conditions outside of the vehicle; and a reporting module configured to, based on the present driver's licensing level of the driver, selectively generate a report including at least one of the first and second occurrences.

In a computer-implemented method, data about potential vehicle operator impairment is retrieved. The data is generated by monitoring a vehicle operator with a first sensor, monitoring the environment ahead of the vehicle with a second sensor, and monitoring force in one or more directions with a third sensor. A plurality of scores is assigned. Each of the plurality of scores corresponds to a respective impairment indicator, and wherein each of the plurality of scores is based on the data about potential operator impairment. An impairment score is generated by performing a mathematical operation on the plurality of scores. It is determined whether the vehicle operator is impaired by comparing the impairment score to a threshold value. Recommendations to reduce operator impairment of the vehicle operator are identified by analyzing the data about potential vehicle operator impairment.

A vehicle or a mobile device within or near the vehicle can have multiple sensors to sense biometric features of a user or driver, and electronic circuitry (such as a computing system) can classify the user or driver according to the sensed biometric features. Also, non-biometric factors of the user or driver or of the mobile device of the user or driver can be used to classify the user or driver, e.g., MAC address, RFID, username and password, PIN, etc. Also, factors from interaction with a user interface of the vehicle or the mobile device can be used to classify the user or driver. Such features and factors can be used alone or in combination for the classification, and the classification can use AI (such as an ANN). The vehicle or the mobile device can then selectively enable or disable features of the vehicle based on the classification.

A driver monitor system and method for predicting impairment of a user of a vehicle. The system includes video cameras, an input device for inputting a list of medications being taken by the driver. Processing circuitry predicts side effects of the medications based on the half-life of the medication, detecting eye gaze movement, eye lid position, and facial expression of the user using images from the video camera, predicting whether the user is transitioning into an impaired physical state that is a side effect of the medications, verifying the side effect of the medications, determining whether the user is fit to drive using the verified side effects of the medications, and outputting to the vehicle an instruction to operate the vehicle in a level of automation that makes up for the at least one side effect or to perform a safe pull over operation of the vehicle.

A vehicle includes a processing device that detects an authentication device approaching the vehicle, determines a user's impaired state based on user condition information acquired using at least one device mounted on the vehicle, and performs a safe driving assistance service. The safe driving assistance service can prevent an impaired user from operating the vehicle.

Exhaustive driving analytical methods, systems, are apparatuses are described. The methods, systems, are apparatuses relate to utilizing partially available data associated with driver and/or driving behaviors to determine safety factors, identify times to react to events, and contextual information regarding the events. The methods, systems, and apparatuses described herein may determine, based on a systematic model, reactions and reaction times, compare the vehicle behavior (or lack thereof) to the modeled reactions and reaction times, and determine safety factors and instructions based on the comparison.