A control apparatus is provided, including: an other-vehicle emotion acquiring unit configured to acquire an other-vehicle emotion indicating an emotion of an occupant of a second vehicle different from a first vehicle; a determination unit configured to determine whether to perform notification to an occupant of the first vehicle based on the other-vehicle emotion; and a notification control unit configured to perform control to notify the occupant of the first vehicle of notification information based on the other-vehicle emotion when the determination unit determines to perform the notification.

The present disclosure relates to a method and a device for recognizing speech in a vehicle. The method for recognizing the speech in the vehicle may include collecting one or more types of information, determining information to be linked with each other for speech recognition based on an information processing priority predefined corresponding to each type of the collected information, analyzing the determined information to perform the speech recognition for a signal input through a microphone, and extracting at least one of a wake up voice or a command voice through the speech recognition to control the vehicle. Therefore, the present disclosure has an advantage of more accurately performing the speech recognition by linking collected various information in the vehicle with each other.

The technology relates to cargo vehicles. National, regional and/or local regulations set requirements for operating cargo vehicles, including how to distribute and secure cargo, and how often the cargo should be inspected during a trip. However, such regulations have been focused on traditional human-driven vehicles. Aspects of the technology address various issues involved with securement and inspection of cargo before a trip, as well as monitoring during the trip so that corrective action may be taken as warranted. For instance, imagery and other sensor information may be used to enable proper securement of cargo before starting a trip. Onboard sensors along the vehicle monitor the cargo and securement devices/systems during the trip to identify issues as they arise. Such information is used by the onboard autonomous driving system (or a human driver) to take corrective action depending on the nature of the issue.

The technology relates to cargo vehicles. National, regional and/or local regulations set requirements for operating cargo vehicles, including how to distribute and secure cargo, and how often the cargo should be inspected during a trip. However, such regulations have been focused on traditional human-driven vehicles. Aspects of the technology address various issues involved with securement and inspection of cargo before a trip, as well as monitoring during the trip so that corrective action may be taken as warranted. For instance, imagery and other sensor information may be used to enable proper securement of cargo before starting a trip. Onboard sensors along the vehicle monitor the cargo and securement devices/systems during the trip to identify issues as they arise. Such information is used by the onboard autonomous driving system (or a human driver) to take corrective action depending on the nature of the issue.

This application provides an in-vehicle user positioning method, an in-vehicle interaction method, a vehicle-mounted apparatus, and a vehicle. In an example, the in-vehicle user positioning method includes: obtaining a sound signal collected by an in-vehicle microphone; in response to that a first voice command is recognized from the sound signal, determining a first user who sends the first voice command; and determining an in-vehicle location of the first user based on a mapping relationship between an in-vehicle user and an in-vehicle location.

A pupil detection device includes an eye area image obtaining unit that obtains image data representing an eye area image in a captured image obtained by a camera; a luminance gradient calculating unit that calculates luminance gradient vectors corresponding to respective individual image units in the eye area image, using the image data; an evaluation value calculating unit that calculates evaluation values corresponding to the respective individual image units, using the luminance gradient vectors; and a pupil location detecting unit that detects a pupil location in the eye area image, using the evaluation values.

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 method of operation of a navigation system comprising: receiving multiple frames, including a first frame and a second frame, of images; detecting a traffic sign from the images between the first frame and the second frame based on a sign recognition model; extracting a first image from the first frame and a second image from the second frame; matching the traffic sign is the same in the first image and the second image based on a similarity model; generating a sign location of the traffic sign with an inertial measurement unit reading based on the first image and the second image; and generating a global coordinate for the sign location for displaying on a navigation map.

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.

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.