Systems and methods are described for an adaptive user interface system for a vehicle with an automatic vehicle system. The adaptive user interface system includes a display and an electronic controller. The controller is configured to generate a graphical user interface indicative of operation of the automatic vehicle system, output the graphical user interface on the display, monitor an indicia of a driver's comfort level, and determine, based on the monitored indicia, when the driver is not comfortable with the operation of the automatic vehicle system. In response to determining that the driver is not comfortable with the operation of the automatic vehicle system, the electronic controller modifies the graphical user interface to provide an increased level of detail.

An audio learning system, which is applied to a vehicle and provides a learning content to a user staying in the vehicle in audio manner, includes: a learning element storage unit storing multiple learning elements; an in-vehicle duration estimation unit estimating an in-vehicle duration during which the user is in the vehicle; a learning program generation unit generating one batch of a learning program to be completed within the in-vehicle duration estimated by the in-vehicle duration estimation unit by combining the plurality of learning elements; and an execution unit executing the learning program. When a driving load estimated by a driving load estimation unit is higher than a predetermined load, the learning program generation unit generates the learning program to mainly include the learning elements that have been executed.

An audio learning system, which is applied to a vehicle and provides a learning content to a user staying in the vehicle in audio manner, includes: a learning element storage unit storing multiple learning elements; an in-vehicle duration estimation unit estimating an in-vehicle duration during which the user is in the vehicle; a learning program generation unit generating one batch of a learning program to be completed within the in-vehicle duration estimated by the in-vehicle duration estimation unit by combining the plurality of learning elements; and an execution unit executing the learning program. When a driving load estimated by a driving load estimation unit is higher than a predetermined load, the learning program generation unit generates the learning program to mainly include the learning elements that have been executed.

The invention regards a method and a system for assisting a driver in driving a vehicle, as well as a vehicle with such system being mounted thereon. Information on an environment of a vehicle is obtained by sensing the environment. Furthermore, information on applicable traffic rules is obtained. A request from a driver is determined from sensing at least one of a driver's utterance, gestures, gaze and operation of vehicle control. The traffic scene as sensed is assessed on the basis of the environmental information, the applicable traffic rules and the determined driver request. Information as requested to be output is generated in response to the determined request of the driver. Finally the information in response to the request from the driver is output.

A hybrid vehicle includes a controller configured to control an engine and an electric motor in one of a plurality of control modes. The controller is configured to execute a switching control to switch the control mode in accordance with a traveling plan. The controller is configured to report at least one of first information and second information using a report device, the first information indicating that the switching control is capable of being executed, the second information indicating that the switching control is not executed. The controller is configured to report third information using the report device in a case where the first information is reported by the report device, the third information being relevant to the switching control, and not to report the third information in a case where the second information is reported by the report device.

The present disclosure relates to a method for controlling at least one drive assistance system of a motor vehicle, a device for carrying out the steps of this method and a system including such a device. The disclosure also relates to a motor vehicle including such a device or such a system.

A vehicle is provided that comprises two or more radio frequency (RF) antennas and two or more RF transceivers to communicate wirelessly sensitive information associated with a user of the vehicle (the two or more RF antennas being at different physical locations on an exterior of the vehicle). The vehicle determines which one of the two or more RF antennas is receiving a strongest signal from a common signal source, selects a first RF transceiver associated with the RF antenna with the strongest signal to send the sensitive information associated with the user to the common signal source, and sends the sensitive information associated with the user to the first RF transceiver for transmission to the common signal source.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

The present disclosure is generally related to a data processing system to validate vehicular functions in a voice activated computer network environment. The data processing system can improve the efficiency of the network by discarding action data structures and requests that invalid prior to their transmission across the network. The system can invalidate requests by comparing attributes of a vehicular state to attributes of a request state.