Provided are methods for vehicle state estimation based on sensor data, which can include receiving the sensor data generated by one or more sensors, calculating a cornering stiffness value associated with the vehicle, predicting a lateral velocity value associated with the vehicle based on the cornering stiffness value, and outputting a set of vehicle state variables indicative of a current state of the vehicle at least by inputting the lateral velocity value into a recursive filter. Some methods described also include updating the cornering stiffness value based on the set of vehicle state variables, updating the lateral velocity value based on the updated cornering stiffness value, and updating the set of vehicle state variables based on the updated lateral velocity value. Systems and computer program products are also provided.

A vehicle may have actuators, including a drive device with a drive motor that can act on a drive wheel, a brake device with a brake that can act on a drive wheel, and/or a steering device with a steering sensor by way of which the steering angle of a wheel is adjustable, a vehicle movement controller, and a setpoint value input means, a setpoint value processing means for detecting setpoint value settings of the setpoint value input means, to calculate a yaw acceleration setpoint value and translational acceleration setpoint values from the setpoint value settings. The setpoint value processing means may be configured to transfer the calculated yaw acceleration setpoint value and translational acceleration setpoint values to the vehicle movement controller, which is configured to actuate one or more of the actuators such that the yaw acceleration setpoint value and the translational acceleration setpoint values are reached.

A vehicle includes a controller that identifies a target around the vehicle and calculates a danger range of the identified target, based on processing surrounding data obtained by sensor devices; calculates a danger range of the vehicle based on processing driving data obtained by sensor devices; determines a danger of collision based on the danger range of the target and the danger range of the vehicle, and control a driving apparatus based on the determined danger of collision. Such a vehicle and a control method thereof can make it possible to avoid a collision based on a danger range by calculating the danger range between the vehicle and a surrounding object of the vehicle depending on a factor causing uneasiness of a user.

An autonomous driving apparatus for generating an intersection path reflecting a driving record may include: a path generating device that generates information on a first path for driving of an autonomous vehicle at an intersection; a path comparison operating device that generates offset information between the generated information on the first path and information on a second path along which the autonomous vehicle is driving; a comparison operation evaluating device that determines whether to store the information on the second path based on the generated offset information; and a comparison operation storage that stores the information on the second path and the offset information based on the determination of whether to store the information on the second path.

A motor-vehicle path-controlling module is arranged to model the path of the vehicle during a change in traffic lane by a Bezier curve relating a value of a parameter to a value of a lateral deviation of the vehicle from the center of a traffic lane and to a value of a time-dependent variable representative of the variation in the change of path; determine a setpoint state vector of a closed feedback loop of a path-controlling device, the loop being designed to control the motor vehicle so that it follows the path modelled by the Bezier curve, the vector being determined on the basis of the lateral deviation, of the time-dependent variable and of the parameter, and transmit the setpoint state vector to the input of the loop.

An apparatus and a method for controlling motion of a vehicle to improve turning motion performance are provided. The processor determines a riding position of a user, receives information about a steering angle of the vehicle, and outputs a vehicle control signal with regard to turning motion performance according to at least one of a phase difference between a yaw rate and lateral acceleration or a lateral slip angle with respect to the riding position, based on the received steering angle. A controller controls the vehicle in accordance with the vehicle control signal. The apparatus provides a passenger of the vehicle with optimal turning motion performance.

A system for controlling an autonomous vehicle includes a memory configured to store parameters of a g-g plot defining admissible space of values of longitudinal and lateral accelerations. The g-g plot parameters define a mapping between user driving preferences and constrained control of the autonomous vehicle. The g-g plot parameters include a maximum forward acceleration, a maximum backward acceleration, a maximum lateral acceleration and a shape parameter defining profile of curves connecting maximum values of forward, backward, and lateral accelerations. The system accepts a comfort level as a feedback from a passenger of the vehicle, determines a dominant parameter corresponding to the feedback, updates the dominant parameter of the g-g plot based on the comfort level indicated in the feedback, and controls the vehicle to maintain dynamics of the vehicle within the admissible space defined by the parameters of the updated g-g plot.

An apparatus for providing a traveling in a vehicle is provided. The apparatus includes a plurality of sensors configured to obtain information about the vehicle and information about an external object, a steering device, an input device configured to receive a lane change command from a driver of the vehicle, and a control circuit configured to be electrically connected with the one or more sensors, the steering device, and the input device. The control circuit is configured to control the vehicle to travel along a deviated path in a driving path of the vehicle based on at least one of the information obtained by the plurality of sensors or an operation of the steering device, to complete a lane change, and to control the vehicle to travel along a deviated path in a target lane of the changed lane in response to the received lane change command.

A slope estimation device estimates a slope of a vehicle traveling road, and includes an input section that acquires a detected value of an acceleration sensor for detecting acceleration in a front-back direction of the vehicle, a centripetal force detecting section that detects centripetal force acting on the acceleration sensor due to a turning motion of the vehicle, and a slope computing section that computes the slope of the vehicle traveling road based on the detected value of the acceleration sensor. When the vehicle is in the turning motion, the slope computing section computes the slope of the traveling road by determining a component of the centripetal force superimposed on the detected value of the acceleration sensor based on a turning center position of the vehicle, a gravity center position of the vehicle, and an installation position of acceleration sensor, and subtracting the component of the centripetal force from the detected value of the acceleration sensor.

Methods and systems implemented in a vehicle involve obtaining a single camera image from a camera arranged on the vehicle. The image indicates a heading angle ψ.sub.0 between a vehicle heading x and a tangent line that is tangential to road curvature of a road on which the vehicle is traveling and also indicates a perpendicular distance y.sub.0 from a center of the vehicle to the tangent line. An exemplary method includes obtaining two or more inputs from two or more vehicle sensors, and estimating kinematic states of the vehicle based on applying a Kalman filter to the single camera image and the two or more inputs to solve kinematic equations. The kinematic states include roll angle and pitch angle of the vehicle.