Systems and methods for personalizing adaptive cruise control in a vehicle are disclosed herein. One embodiment collects vehicle-following-behavior data associated with a particular driver; trains a Gaussian Process (GP) Regression model using the collected vehicle-following-behavior data to produce a set of adaptive-cruise-control (ACC) parameters pertaining to the particular driver, the set of ACC parameters modeling learned vehicle-following behavior of the particular driver; generates an acceleration command for the vehicle based, at least in part, on the set of ACC parameters; applies a predictive safety filter to the acceleration command to produce a certified acceleration command that has been vetted for safety; and controls acceleration of the vehicle automatically in accordance with the certified acceleration command to regulate a following distance between a lead vehicle and the vehicle in accordance with the learned vehicle-following behavior of the particular driver.

A hybrid deterministic override to cloud based probabilistic advanced driver assistance systems. Under default driving conditions, an ego vehicle is controlled by a probabilistic controller in a cloud. An overall gap between the ego vehicle and a leading vehicle is divided into an emergency collision gap and a driver specified gap. The vehicle sensors monitor the overall gap. When the gap between the ego vehicle and the leading vehicle is less than or equal to the emergency collision gap, a deterministic controller of the ego vehicle overrides the cloud based probabilistic controller to control the braking and acceleration of the ego vehicle.

A control device for a vehicle includes an upper limit value setting unit configured to set an upper limit value of an acceleration or deceleration of the vehicle, and a vehicle controller configured to control the vehicle such that the acceleration or deceleration does not exceed the upper limit value. The upper limit value setting unit is configured to change the upper limit value according to at least one predetermined condition.

A driving limitation system includes the steps of: identifying a driver by a driver authentication means; extracting information on the identified driver; extracting data relating to vehicle speed limitation according to the driver; extracting data relating to limitation in a vehicle traveling area according to the driver; performing selection or generation of map data regarding a traveling area; generating, on the basis of the extracted data relating to the vehicle speed limitation, vehicle traveling area limitation and the driver, a traveling speed control command within the limitation in the vehicle traveling area in accordance with the physical ability and/or cognitive ability of the driver; transmitting the traveling speed control command to a vehicle speed control means; generating a control command for controlling the vehicle speed on the basis of the safety speed indicated by the vehicle speed control means; and sending the control command to an engine and to a braking system to set the traveling speed of the vehicle to be equal to or lower than the safety speed according to the driver.

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 for setting a tuning parameter for an Automated Driving System (ADS) of a vehicle is disclosed. A corresponding non-transitory computer-readable storage medium, vehicle control device and a vehicle comprising such a control device are also disclosed. The method comprises receiving environmental data from a perception system of the vehicle, said environmental data comprising a plurality of environmental parameters, determining, by means of a self-learning model, an environmental scenario based on the received environmental data; setting the tuning parameter for the ADS based on the self-learning model and the determined environmental scenario, the tuning parameter defining a dynamic parameter of the ADS, receiving at least one signal representative of a vehicle user feedback on the set tuning parameter, and updating the self-learning model for the set tuning parameter for the identified environmental scenario based on the received vehicle user feedback.

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.

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.

An estimation apparatus of the disclosure includes a determiner that determines whether or not an attention target is visually recognizable from a driver of a vehicle based on information related to a visual field range of the driver; and an estimator that estimates a visual field abnormality of the driver based on a driving operation of the driver in a case where the determiner determines that the attention target is visually recognizable from the driver.

A method and a system of deploying ignition interlock device functionality. The method comprises receiving data in authentication of a user account associated with the IID; rendering a user interface at the mobile computing device, the user interface including indication of a status of the user account associated with the IID; and receiving a selection of a user action responsive to the status of the user account associated with the IID.