This document describes target curvature estimation considering vehicle dynamics constraints. Some vehicle dynamics models use several kinematic states to predict the paths of targets identified by an object-tracking system. Rather than rely on predetermined industry measurements as the kinematic inputs to a model, an example system instead estimates some of these states using near real-time data output from a tracking filter. This can include estimating position and velocity states, as well as curvature and centripetal acceleration states. The example system is particularly suited at accurately predicting the curvature and centripetal acceleration states, which greatly improves the accuracy of the object-tracking system, and further improves safety in avoiding a target collision.

Systems and methods for vehicle motion control are provided. The method includes: calculating a correction factor using one of three different sets of operations when the vehicle is performing a limit handling maneuver, wherein the correction factor is calculated using a first set of operations when the vehicle is operating in an understeer state, calculated using a second set of operations when the vehicle is operating in an oversteer state, and calculated using a third set of operations when the vehicle is operating in a neutral steer state; adjusting a desired lateral acceleration and a desired yaw rate by applying the correction factor to account for a reduced level of friction experienced by the vehicle when traveling on a non-ideal friction surface; calculating optimal control actions based on the adjusted desired lateral acceleration and adjusted desired yaw rate; and applying the optimal control actions with vehicle actuators during vehicle operations.

A vehicle and a system and method of controlling the vehicle. The system includes a sensor and a processor. The sensor obtains a first estimate of a force on a tire of the vehicle based on dynamics of the vehicle. The processor is configured to obtain a second estimate of the force on the tire using a tire model, determine an estimate of a coefficient of friction between the tire and the road from the first estimate of the force and the second estimate of the force, and control the vehicle using the estimate of the coefficient of friction.

In motion control in the present invention, operation amounts relating to braking and drive are set as a control command when a difference between a physical quantity relating to a target vehicle attitude which is based on a target trajectory and a physical quantity relating to a linear model vehicle attitude which is based on a linear model of a vehicle exceeds a threshold value, operation amounts relating to braking and steering are set as the control command when the difference is equal to or smaller than the threshold value, and an attitude of the vehicle in a yaw direction is controlled based on the control command.

A method for determining the values of parameters for a controller of a vehicle, wherein respective error measures are calculated for different sets of values and a set of values is selected based on the error measures.

A vehicle stability control method includes collecting steering information from a sensor of a vehicle, calculating a saturation index of a front axle of the vehicle or a rear axle of the vehicle using the steering information, and controlling an application of the vehicle based on the saturation index.

A method is for determining a side slip angle during the cornering of a vehicle. The following variables are recorded and interlinked via a mathematical vehicle model with assumptions of the linear single-track model: a predetermined or measured position of the center of gravity between a front and rear axle, the current vehicle velocity, a current vehicle cornering motion variable, the current steering angle on the front axle. To simplify the determination of the side slip angle, it is determined under the assumption that the difference between the side slip angle and the Ackermann side slip angle is proportional to the difference between the Ackermann angle and the steering angle. The actual side slip angle is deduced from the relationship of the measured steering angle and the Ackermann angle based on the proportionality relationship of the Ackermann side slip angle theoretically present when driving through the same curve without slip.

A vehicle positioning method via data fusion and a system using the same are disclosed. The method is performed in a processor electrically connected to a self-driving-vehicle controller and multiple electronic systems. The method is to perform a delay correction according to a first real-time coordinate, a second real-time coordinate, real-time lane recognition data, multiple vehicle dynamic parameters, and multiple vehicle information received from the multiple electronic systems with their weigh values, to generate a fusion positioning coordinate, and to determine confidence indexes. Then, the method is to output the first real-time coordinate, the second real-time coordinate, and the real-time lane recognition data that are processed by the delay correction, the fusion positioning coordinate, and the confidence indexes to the self-driving-vehicle controller for a self-driving operation.

In a method for front-rear driving torque distribution of a vehicle, a controlling apparatus determines an expected status parameter existing during steering of a vehicle based on a wheel angle of the vehicle. The controlling apparatus determines a current correction yawing moment based on an actual status parameter existing during the steering of the vehicle and the expected status parameter, and determines a mapping relationship between a correction yawing moment and a torque distribution coefficient based on the wheel angle and acceleration information of the vehicle. The controlling apparatus then determines a torque distribution coefficient of the vehicle based on the current correction yawing moment and the mapping relationship, and determines front and rear axle driving torques of the vehicle based on the torque distribution coefficient of the vehicle.

A steering control device which calculates a steering control amount for controlling steering of a vehicle includes a basic control amount calculation unit which calculate a basic control amount, and a steering control amount arithmetic unit which calculates the steering control amount with reference to self-aligning torque caused by a motion state amount of the vehicle and the basic control amount.