A system includes a first notifying unit, a detection unit, and a second notifying unit. The first notifying unit performs a first notification for notifying a target in a predetermined area of an abnormality, in a case where an abnormal state occurs in a running vehicle. The detection unit detects presence of a target unaware of the first notification. The second notifying unit performs a second notification for notifying the target in the predetermined area of the abnormality, in a case where the presence of the target unaware of the first notification is detected.

A method for detecting drowsiness of a driver for a driver assistance system of a vehicle includes reading in at least a first indicator signal that represents a first drowsiness parameter of the driver determined by a first drowsiness-detection device of the vehicle, and a second indicator signal that represents a second drowsiness parameter of the driver determined by a second drowsiness-detection device of the vehicle, and optionally a third indicator signal that represents a third drowsiness parameter of the driver determined by a third drowsiness-detection device of the vehicle; ascertaining validities of the indicator signals; and determining a drowsiness signal that represents the detected drowsiness of the driver utilizing the indicator signals and the validities.

Provided is a vehicle seat that detects an alertness level of the driver, urges the driver to be alert, and permits the transition from autonomous driving to manual driving when the driver is alert enough for the manual driving. A vehicle seat (1) configured to be mounted on a vehicle (3) provided with a vehicle control device (5) that can be selectively switched from autonomous driving to manual driving comprises: a seat body (7) configured to support a driver; a seat control unit (10) configured to communicate with the vehicle control device; an alertness level sensor (8) provided on the seat body for detecting an alertness level of the driver; and a rousing unit (9) provided on the seat body for providing a stimulus for urging the driver to be roused, wherein the seat control unit is configured to detect the alertness level of the driver according to a signal from the alertness level sensor upon receiving a start signal that is produced by the vehicle control device when a transition from the autonomous driving to the manual driving is to be initiated, to activate the rousing unit when the alertness level is lower than a first alertness level threshold value, and to permit the vehicle control device to perform the transition from the autonomous driving to the manual driving when the alertness level is equal to or higher than the first alertness level threshold value.

A driver status monitor test method is for testing if a driver status monitor generates an alarm operation in accordance with driver motion images. A photographing unit of the driver status monitor is configured to take photographs of the driver motion images. The driver status monitor test method includes a test motion selecting step and a driver motion image displaying step. The test motion selecting step includes selecting at least one test motion for testing the driver status monitor by a user interface. The driver motion image displaying step includes displaying the driver motion images by a display. The driver motion images are a plurality of predetermined image frames in accordance with the test motion. The driver motion images include at least one of a face image, a forelimb image and a torso image.

A vehicle safety support apparatus includes: a driver monitoring sensor configured to monitor a driver; an external environment monitoring sensor configured to monitor an external environment of a vehicle; a driver input filtering unit configured to filter a vehicle control input from the driver; and at least one processor connected to the driver monitoring sensor, the external environment monitoring sensor, and the driver input filtering unit, the at least one processor configured to: determine criterion based on data acquired from the driver monitoring sensor and the external environment monitoring sensor; determine whether to take over a driving control of the vehicle in response to the data acquired from the driver monitoring sensor and the external environment monitoring sensor meeting the criterion; and perform autonomous driving to move the vehicle to a safe area in response to determining to take over the driving control from the driver.

A vehicle sound output device including: an acquiring section configured to acquire wakefulness level information that indicates a degree of a wakefulness state of a driver of a vehicle; and a control section configured to, in a case in which the degree of the wakefulness state indicates a decreased level of wakefulness, control a sound output section to output a sound based on at least one of a predetermined frequency, a predetermined tone, or a predetermined content that stimulates a sympathetic nerve of the driver.

The present invention “car driver alcohol level and sleeping status detection and notification system using machine learning programming and IOT-based technology “is a vehicle driver sleepiness monitor, configured as a auto-contained Unit for dashboard unit. The invention is also providing for individual driver interrogation and notification response integrated with defined and fixed unit sensory inputs on vehicle condition and driver control action and translates these inputs into weighing factors to adjust a previous history and biological activity circadian rhythm reference Unit. The invention is also including an in turn to provide a vibration, water spray and audio-visual sleepiness warning alert and an automatic dialog system capable of keeping a drive awake while driving during a long trip or one that extends into the late evening. The invented system also warns the driver or changes the topic of conversation if the system determines that the driver is about to fall asleep and the system may also detect whether a driver is effected by alcohol or drugs or any other activity. The invented technology also includes a for drowsiness detection and accident prevention using Raspberry Pi. This system is an auto rune a real-time system which captures high resolution image continuously and measures the state of the eye movement according to the specified algorithm and gives a warning if required.

A method for switching modes for operating a vehicle, a non-transitory computer-readable medium for performing the method, and information processing apparatuses. The method includes determining, by circuitry of an information processing apparatus, whether a mode for operating the vehicle is to be switched from one of autonomous and manual driving modes to the other of the autonomous and manual driving modes. A state of a driver of the vehicle is obtained when the mode for operating the vehicle is determined to be switched. The method further includes switching, by the circuitry, the mode for operating the vehicle from the one of the autonomous and manual driving modes to the other of the autonomous manual driving modes based on the obtained state of the driver.

A vehicle safety support apparatus includes: a driver monitoring sensor configured to monitor a driver; an external environment monitoring sensor configured to monitor an external environment of a vehicle; and at least one processor configured to: determine whether the vehicle is in an immediate hazard situation based on data acquired from the driver monitoring sensor and the external environment monitoring sensor; determine, in response to determining that the vehicle is in the immediate hazard situation, whether to perform a recovery maneuver or a rescue maneuver based on the data acquired from the driver monitoring sensor and the external environment monitoring sensor to get out of the immediate hazard situation; and perform, in response to determining to perform the rescue maneuver, autonomous driving to move the vehicle to a safe area by taking over a driving control from the driver.

A driver condition estimation device includes an estimation unit configured to trigger an event that a webbing of a seat belt device is retracted, and to estimate a condition of a driver based on an amount of retraction of the webbing in the event.