A plurality of driving force transmitting components of the same kind is categorized into a plurality of groups depending on a frequency range with the loudest operation sound. A component selection device stores mapping data that is data that defines mapping learned by machine learning. When the user-related information is input as an input variable, the mapping outputs a value corresponding to the input variable as an output variable. The vehicle component selection method causes the component selection method to execute: an input process inputting the user-related information into the mapping as the input variable; a selection process selecting the group corresponding to the output variable output by the mapping from the groups; and a determination process determining the driving force transmitting component categorized into the group selected in the selection process as a component to be installed in the vehicle for the user identified by the user-related information.

A vehicle control device includes a travel environment recognition device configured to recognize travel environment, a vehicle travel state detection device, and an autonomous/manual driving mode controller. The autonomous/manual driving mode controller includes a learning correction unit configured to store at least one of a plurality of control parameters indicating the vehicle travel state by operation of the driver in the autonomous driving mode, and to correct the control parameter in the autonomous driving mode according to the stored control parameter. When the stored control parameter is the control parameter changed by an operation by the driver midway in passing or after passing, the learning correction unit is configured to correct the control parameter in the autonomous driving mode so that an acceleration level or the deceleration level is increased midway in passing or after passing.

An arousal support device including a processor programmed to output a dialogue speech in a form of a question, and obtain response speech which is a response of a driver to the dialogue speech; measure a response time from when the dialogue speech is output till the response speech is obtained; store the measured response time in a database; derive an estimated value of wakefulness of the driver based on the measured response time and a plurality of response times previously stored in the database; and output a signal corresponding to the estimated value to provide arousal support.

A sensor and/or control device for a vehicle. The sensor and/or control device includes an electronics unit configured to read out and/or establish during at least a single actuation of a brake actuation element of the vehicle by a driver of the vehicle, an adjustment travel of the brake actuation element, an adjustment speed of the brake actuation element and/or an adjustment acceleration of the brake actuation element, based on at least one signal provided to the electronics unit. The electronics unit configured to establish a temporal average and/or a temporal frequency distribution each of the adjustment travel of the brake actuation element, of the adjustment speeds of the brake actuation element and/or of the adjustment accelerations of the brake actuation element as at least part of a piece of driver-characterizing braking and/or driving style information.

A vehicle driving support system evaluates the ability of a driver based on the driving operation of the driver for each of driving-related functions possessed by the driver to drive the vehicle. Based on the past evaluation result, the vehicle driving support system determines whether the ability of the driver is less than a predetermined standard, whether the ability of the driver is not improved from then on, and whether the ability of the driver is on a declining trend for each of the driving-related functions. The vehicle driving support system performs support control for causing the vehicle to support the exertion of the ability of the driver when determining that the ability of the driver is less than the predetermined standard and improvable from then on or that the ability of the driver is equal to or more than the predetermined standard and is on a declining trend.

A vehicle driving support system evaluates the ability of a driver based on the driving operation of the driver for each of a plurality of driving-related functions possessed by the driver to drive the vehicle. In addition, the vehicle driving support system determines whether the ability of the driver is less than a predetermined standard for each of the driving-related functions and is not improved from then on, based on the past evaluation result of the ability of the driver. When determining that the ability of the driver is less than the predetermined standard for at least a part of the driving-related functions and is not improved from then on, the vehicle driving support system performs substitution control that causes a vehicle to perform the part of the driving-related functions instead so as to perform driving even if the driver does not exert the ability.

Provided herein is a method for assisting a driver with driving a motor vehicle. The method includes ascertaining a permissible driving speed in a route section by evaluating environmental data describing the motor vehicle environment. The method further includes calculating a target maximum speed, which is lower than the permissible driving speed, by subtracting a predefined reduction amount from the permissible driving speed and/or by multiplying the permissible driving speed by a predefined scaling factor. The method further includes controlling at least one alert device for outputting an alert to the driver when a present driving speed of the motor vehicle exceeds the target maximum speed and/or controlling the driving speed of the motor vehicle by a longitudinally guiding driver assistance system, wherein the target maximum speed is used as a maximum speed or as a target speed.

Disclosed are an audio information transmission system, method, and apparatus, and a corresponding two-wheeled vehicle and helmet. The system includes a media control apparatus and an audio switching apparatus connected to the media control apparatus. The audio switching apparatus is connected to a mobile terminal and the helmet and is configured to receive first audio information transmitted by the mobile terminal and transmit same to the media control apparatus. The media control apparatus is configured to receive and mix second audio information generated by the two-wheeled vehicle with the first audio information, to generate mixed audio information. The audio switching apparatus transmits the mixed audio information to the helmet. In the present application, the audio information transmitted by the mobile terminal and information such as navigation voices, alarms emitted by the two-wheeled vehicle are mixed. The mixed audio information is transmitted to the helmet, so that the user can obtain both the audio information transmitted by the user terminal and the navigation voices transmitted by the electric vehicle, without switching between the audio information from the mobile terminal and the navigation voices emitted by the electric vehicle. The user's driving safety is improved and the user experience is enhanced.

A navigation system for a host vehicle is provided. The system may comprise at least one processing device comprising circuitry and a memory. The memory includes instructions that when executed by the circuitry cause the at least one processing device to: receive a plurality of images acquired by a camera, the plurality of images being representative of an environment of the host vehicle; analyze the plurality of images to identify a presence in the environment of the host vehicle a navigation rule suspension condition; temporarily suspend at least one navigational rule in response to identification of the navigation rule suspension condition; and cause at least one navigational change of the host vehicle unconstrained by the temporarily suspended at least one navigational rule.

A vehicle risk analysis system, includes: a historical database, storing the sensing data and accident records acquired from multiple sampled vehicles into big data; a learning unit, connected to the historical database for analyzing the relationship between accident records and driving scenarios, to generate a risk classification model, which can further predict the risk of accidents for a vehicle in-use; and a risk profiling unit, receiving the risk classification model from the learning unit and acquiring the sensing data from the vehicle in-use, to generate a risk profile for the vehicle in-use under different driving modes. The risk profile reports the expected risks of accidents under different driving modes by using the occurrence rates for different driving scenarios and the expected losses of money caused by accidents, wherein each of the driving scenarios can be determined by a combination of the sensing data. The system can suggest an optimal driving mode for the vehicle in-use by using the risk profile, which can be further used to price the insurance premiums under different driving modes.