A driving support apparatus according the embodiment includes: a determination unit that determines driving support control having a driving support resource amount that is capable of assuring required resources with respect to a resource amount that is capable of being assured by a level of a vehicle driver's concentration on driving, the required resources being assumed to be required for safe driving; and a driving support unit that changes the driving support control to be performed to driving support control that is determined by the determination unit to be capable of assuring the required resources.

Provided is a method for use by a driving assistance apparatus that assists a transition from an autonomous driving mode in which a vehicle is driven under autonomous control to a manual driving mode in which the vehicle is driven by a driver. The method includes: detecting an activity by the driver; detecting conditions of the driver; and determining a take-over request method which is a method of presenting, in the vehicle, a take-over request that informs the driver that the autonomous driving mode is going to be cancelled, the determining being based on at least the detected activity by the driver and the detected conditions.

Methods, systems, apparatuses, and computer program products are provided for altering the behavior of an electronic personal assistant based on a situation associated with a mobile device. A situation is sensed with a plurality of sensors to generate sensor data. A situation score is calculated based on the sensor data. Behavior of an electronic personal assistant is altered based on the calculated situation score. In one aspect, the situation is a driving situation in which a driver drives a vehicle on a roadway. In such case, a driving situation score is calculated based on the sensor data, and behavior of the electronic personal assistant is altered based on the calculated driving situation score, such as suspending interactions by the electronic personal assistant with the driver to avoid the driver being distracted.

Systems and methods for improving vehicle wrong-way detection including systems, sensors or features, such as those for system/network clocks, ambient light, driver impairment, automatic cruise control, blind spot warning or configurable vehicle security, either singly or in any combination therewith, may refine and/or modify the confidence level of detecting particular or potential wrong-way incidents. By modifying the confidence level, the system may change the system sensitivity by moving the cutoff point at which an alert activation takes place. The systems described above can modify the wrong-way detection sensitivity. Greater confidence, or system sensitivity, may also help enable the system to take further actions beyond a simple warning. At greater confidence levels, the system could intervene, by way of a non-limiting example, with throttle limiting, turning on the hazard lights or even bringing the vehicle to a stop.

The present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle by comparing current image feature data to previously classified image features.

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.

There is provided, in a vehicle capable of accommodating a plurality of passengers, a display system capable of providing a motivation to start a conversation among the passengers in view of conversation intentions of each passenger. The display system includes a control device, and at least one display device. The control device is configured to perform a conversation desire display process to display a conversation desire level of each of the passengers. Alternatively, the control device is configured to perform a conversation intention display process to display a conversation intention of each of the passengers for the other passengers. The conversation desire level and the conversation intention among passengers are input to the input device provided in the display system, by an operation of the passenger. Alternatively, they are estimated by the control device based on the passenger state information detected by the sensor provided in the display system.

An approach for adjusting driving parameters of an AV (autonomous vehicle) based on the driving style of the passenger is disclosed. The approach utilizes existing driving patterns of the passenger and perform a dynamic comparison and correlation with safe driving patterns of the passengers themselves. Based on that evaluation, the approach would suggest the parameters for adjusting the AV driving style in order to ensure AV riding experience meets the expected level of safe and stress-less riding. Furthermore, the approach can dynamically adjust the driving style during the trip based on the reaction and feedback from the passenger.

Provided are an apparatus and method for monitoring driver's concentrativeness capable of monitoring whether a driver is concentratedly obtaining major information by tracing a driver's sight while a vehicle is running, in order to provide alarm to the driver when driver's concentrativeness is dropped at a time when the major information is changed while the vehicle is running.

In accordance with one embodiment of the present disclosure, a method includes generating a plurality of icons, wherein each icon has a target frequency unique from each other, receiving brain activity data based on an epoch, generating a reference signal based on the epoch, calculating correlation coefficients between the brain activity data and the reference signal, wherein the correlation coefficients are calculated in a window that is within ±0.5 Hz of the target frequencies, including endpoints, determining a confidence score based on the correlation coefficients and the epoch, and determining a selected icon among the plurality of icons based on the correlation coefficients in response to the confidence score surpassing a threshold confidence score.