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.

An adaptive cruise control system includes an information acquisition unit having a main detector and a secondary detector, a control unit, and an execution unit. The main detector detects an object located ahead of the vehicle. The control unit determines whether control of the vehicle is required depending on an actual value determined by the main detector and the threshold value of a system property characterizing the driving environment. The execution unit controls the vehicle. The secondary detector is arranged such that its field of view for detecting an object located at an angle ahead of the vehicle covers the boundary of the main detector's field of view, and which is oriented outwards in relation to the forward direction of the vehicle. The secondary detector sends an indication signal to adjust the threshold value of the system property when an object is detected.

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 system includes a processor and a memory storing instructions executable by the processor to control at least one of a steering system or a propulsion system to operate a vehicle at a speed below a speed threshold. The instructions include instructions to determine whether one or more second vehicles a first distance from the vehicle are traveling below the speed threshold. The instructions include instructions to, upon determining the second vehicles are traveling below the speed threshold, continue to control the steering system or the propulsion system. The instructions include instructions to, upon determining the second vehicles are not traveling below the speed threshold, transition control of the steering system or the propulsion system to a human operator of the vehicle.

A control system for a vehicle includes an engine controller operable to determine a requested engine torque in response to a cruise control set command and a cruise control offset value, determine an engine torque command in response to the requested engine torque and a torque limit, and control operation of an engine in response to the engine torque command. The control system also includes a platooning controller operable to determine and provide to the engine controller the cruise control set command, the cruise control offset value and the torque limit effective to cause the engine controller to control the engine to provide a desired following distance between the vehicle and a second vehicle.

System and techniques for test scenario verification, for a simulation of an autonomous vehicle safety action, are described. In an example, measuring performance of a test scenario used in testing an autonomous driving safety requirement includes: defining a test environment for a test scenario that tests compliance with a safety requirement including a minimum safe distance requirement; identifying test procedures to use in the test scenario that define actions for testing the minimum safe distance requirement; identifying test parameters to use with the identified test procedures, such as velocity, amount of braking, timing of braking, and rate of acceleration or deceleration; and creating the test scenario for use in an autonomous driving test simulator. Use of the test scenario includes applying the identified test procedures and the identified test parameters to identify a response of a test vehicle to the minimum safe distance requirement.

Provided is a vehicle control device capable of preventing a delay in driver's bank angle operation during traveling of a straddle type vehicle on a curve and enhancing safety of the vehicle. The vehicle control device 100 is a device that is mounted on a two-wheeled motor vehicle and controls the vehicle to travel while following a preceding vehicle. The vehicle control device 100 includes a curvature acquisition unit 110 that acquires a curvature of a road in front of the vehicle and a driving force control unit 120 that limits a change amount of driving force of the vehicle per unit time based on the curvature acquired by the curvature acquisition unit 110.

A vehicle driving assistance apparatus predicts (i) a first consumed energy amount corresponding to a consumed energy amount consumed by a driving apparatus of an own vehicle when executing a first following control and (ii) a second consumed energy amount corresponding to the consumed energy amount consumed by the driving apparatus of the own vehicle when executing the second following control. The apparatus executes the second following control when the second consumed energy amount is smaller than the first consumed energy amount. On the other hand, the apparatus executes the first following control when the second consumed energy amount is equal to or greater than the first consumed energy amount.

A vehicle speed controlling apparatus comprising a driving mode selector configured to receive a selection of a periodic-speed driving mode from a user, a driving strategy control unit including a speed profile generator configured to generate a periodic-speed driving speed profile with a period, an amplitude, and an average speed, and a driving assistance unit configured to output a required torque for a driving motor to follow the periodic-speed driving speed profile.

A method of controlling movement of multi-vehicle includes acquiring a constraint condition under which vehicles move and a calculation cycle for calculating movement routes of the vehicles; acquiring a position of each vehicle; specifying a target position for each vehicle; calculating, based on the position of each vehicle, the target position, and the constraint condition, a movement route for prediction steps of each vehicle; determining, based on the movement routes of the vehicles, a driving condition of each vehicle from a current time to a unit time; and controlling movement of each vehicle. Calculating the movement route including performing optimization calculation based on an evaluation function, evaluation of which becomes higher as a deviation between the vehicle and the target position for each prediction step becomes smaller, and the constraint condition, to calculate the movement route.