A driving assistance device 1 is provided with: three or more detection units 5a to 5d which are configured to detect a likely-to-be-dozing state in which likelihood that a driver of a vehicle is dozing is high by different indices and at prescribed intervals; a state determination unit 34 which determines that the driver is in a dozing state when the likely-to-be-dozing state is detected by at least two of the detection units; and a warning control unit 36 which causes a warning device 6 to issue a warning when the state determination unit 34 determines that the driver is in the dozing state.

A driving assistance device 1 is provided with: three or more detection units 5a to 5d which are configured to detect a likely-to-be-dozing state in which likelihood that a driver of a vehicle is dozing is high by different indices and at prescribed intervals; a state determination unit 34 which determines that the driver is in a dozing state when the likely-to-be-dozing state is detected by at least two of the detection units; and a warning control unit 36 which causes a warning device 6 to issue a warning when the state determination unit 34 determines that the driver is in the dozing state.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

A system for monitoring an acoustic scene outside a vehicle; the system including: a vehicle with wheels and a trunk, an acoustic sensor disposed in the trunk, a control unit operatively connected to the acoustic sensor, and at least one neural network operatively connected to the control unit, and trained in such a way to correlate the characteristics of an audio signal with types of road surfaces; the control unit is configured in such a way to receive an audio signal detected by the acoustic sensor while the vehicle is traveling, extract the characteristics of the audio signal and input said characteristics of the audio signal to the neural network in order to identify the type of road surface covered by the vehicle wheels.

A looking away determination device includes: a looking away determination unit that determines that a driver is in a looking away state when a proportion of an image in which a face having a degree of certainty equal to or greater than a threshold value is shown with respect to a plurality of images obtained by imaging the driver, the degree of certainty serving as an index of face likeness; and an updating unit that updates the threshold value based on a degree of certainty of a face shown in an image obtained by imaging the driver.

An apparatus including an interface and a processor. The interface may be configured to receive video frames corresponding to an interior of a vehicle. The processor may be configured to perform video operations on the video frames to detect objects in the video frames, detect one or more passengers based on the objects detected in the video frames, determine a location of each of the passengers detected and generate a climate control signal for each of said passengers. The climate control signal may be implemented to control climate settings in a plurality of climate zones within the vehicle. The processor may correlate the location of each of the passengers to the climate zones.

An apparatus including an interface and a processor. The interface may be configured to receive video frames corresponding to an interior of a vehicle. The processor may be configured to perform video operations on the video frames to detect objects in the video frames, detect one or more passengers based on the objects detected in the video frames, determine a location of each of the passengers detected and generate a climate control signal for each of said passengers. The climate control signal may be implemented to control climate settings in a plurality of climate zones within the vehicle. The processor may correlate the location of each of the passengers to the climate zones.

A camera for a vehicular vision system includes a circuit board having a first side and a second side opposite the first side. The circuit board has a first coefficient of thermal expansion (CTE). An imager is disposed at the first side of the circuit board, and a lens assembly is optically aligned with the imager. A bend-countering element is disposed at the first side or the second side of the circuit board. The bend-countering element has a second CTE that is different from the first CTE of the circuit board. The bend-countering element counters temperature-induced bending of the circuit board. With the camera disposed at the vehicle, temperature-induced bending of the bend-countering element is in an opposite direction from temperature-induced bending of the circuit board.

A method for controlling a vehicle (100) includes reading-in measurement data about a surface (6) of a substrate (2) lying ahead of the vehicle (100) in its travel direction (F), where the surface contains a ground-level obstacle (4) and recognizing the ground-level obstacle (4) from the measurement data. The method also includes determining a movement vector (V4) of the recognized ground-level obstacle (4) in a vehicle-associated coordinate system on the basis of the measurement data read in and determining a movement vector (V1) of the vehicle (100) in a coordinate system superordinate relative to the vehicle-associated coordinate system. The method further includes checking whether the ground-level obstacle (4) is a dynamic ground-level obstacle (4) in the superordinate coordinate system and emitting a control signal for controlling an operational safety system (30) of the vehicle (100) as a function of the result of the check. Also disclosed is a control unit (200) for carrying out a method of that type and a vehicle (100) with a control unit (200) of that type.

A method for controlling a vehicle (100) includes reading-in measurement data about a surface (6) of a substrate (2) lying ahead of the vehicle (100) in its travel direction (F), where the surface contains a ground-level obstacle (4) and recognizing the ground-level obstacle (4) from the measurement data. The method also includes determining a movement vector (V4) of the recognized ground-level obstacle (4) in a vehicle-associated coordinate system on the basis of the measurement data read in and determining a movement vector (V1) of the vehicle (100) in a coordinate system superordinate relative to the vehicle-associated coordinate system. The method further includes checking whether the ground-level obstacle (4) is a dynamic ground-level obstacle (4) in the superordinate coordinate system and emitting a control signal for controlling an operational safety system (30) of the vehicle (100) as a function of the result of the check. Also disclosed is a control unit (200) for carrying out a method of that type and a vehicle (100) with a control unit (200) of that type.