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.

The present disclosure provides system and methods for a vehicle infotainment system (VIS) to monitor physiological parameters of occupants of a vehicle. The VIS also monitors vehicle operating parameters. The VIS is able to detect when an occupant is experiencing a physiological condition and correlates the physiological condition to one or more vehicle operating parameters. In response to detecting a physiological condition and to determining the correlation, the VIS causes an action to occur in order to mitigate the physiological condition and/or to seek assistance for the physiological condition.

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 system for preventing abnormal acceleration of a vehicle includes a device configured such that in a state in which the vehicle is stopped while the vehicle is turned on, the device is configured to determine whether abnormal acceleration prevention is necessary based on a final destination or a current position of the vehicle before the vehicle is turned off to thereby limit a vehicle speed. The system and a method for preventing abnormal operation of the vehicle can prevent a vehicle accident due to the abnormal acceleration caused by misoperation by a driver, such as misoperation of an accelerator pedal of the vehicle.

An automatic cruise control system for controlling at least a powertrain of a vehicle, the cruise control system being configured to automatically control a vehicle speed to a target speed determined based on a set speed and on information relating to a road topography along an expected travelling route of the vehicle. The automatic cruise control system is configured to: while automatically controlling the vehicle speed to the target speed, receive an indication that a slippery road condition applies or is expected to apply, in response to receiving said indication, activate a predefined slippery road condition driving mode in which predetermined restrictions apply, said restrictions relating to at least one of the vehicle speed, an allowable vehicle acceleration, and a gear selection of the powertrain, control at least the powertrain in accordance with the slippery road condition driving mode.

This application provides a data processing method performed a computer device. The method includes: generating an initial predicted lane change acceleration corresponding to a target vehicle in a current lane; generating target predicted position information corresponding to the target vehicle according to a predicted lane change time duration taken for the target vehicle to change from the current lane to a target lane, the target lane being a lane to which the target vehicle is expected to change to; determining a target obstacle vehicle in the target lane and adjacent to the target vehicle according to the target predicted position information; determining, according to a predicted position relationship between the target obstacle vehicle and the target vehicle, a target predicted lane change acceleration; and controlling, according to the target predicted lane change acceleration, the target vehicle to change from the current lane to the target lane.

A method for coordinating vehicles of a vehicle group, including implementing a setpoint acceleration in each vehicle of a vehicle group by electric control of a drive system or of a braking system of the respective vehicle, observing actual driving dynamics of the vehicles of the vehicle group during the implementation of the setpoint acceleration, assessing the observed actual driving dynamics of the vehicles on the basis of the requested setpoint acceleration for the respective vehicle, and outputting a vehicle-specific assessment result, and determining and outputting an acceleration limit value or a jerk limit value as a function of the vehicle-specific assessment result and adapting the vehicle-specific acceleration parameters in at least one of the vehicles of the vehicle group as a function of the determined acceleration limit value or jerk limit value in order to implement the setpoint acceleration.

An apparatus for controlling a lane change of a vehicle includes: a sensor to sense an external vehicle, an input device to receive a lane change command from a driver of the vehicle, and a control circuit to be electrically connected with the sensor and the input device. The control circuit may receive the lane change command using the input device, calculate a minimum operation speed for lane change control, and determine whether to accelerate the vehicle based on a distance between a preceding vehicle which is traveling on the same lane as the vehicle and the vehicle, when a driving speed of the vehicle is lower than the minimum operation speed when receiving the lane change command.

A travel controller requests a driver of a vehicle to perform a pre-lane-change action required of the driver to make a lane change from a first lane to a second lane adjoining the first lane, and changes the speed of the vehicle with a first acceleration until the driver performs the pre-lane-change action after the request and with a second acceleration having a greater absolute value than the first acceleration after the driver performs the pre-lane-change action, thereby controlling the speed of the vehicle to reduce the distance to a lane change position defined to make the lane change. The lane change position depends on the positional relationship between the vehicle and a moving object on the second lane.