Abstract: A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

Abstract: A method of controlling a vehicle includes obtaining a linear representation of a vehicle dynamics model that includes actuator dynamics u integrated with vehicle dynamics x. The actuator dynamics u include a road wheel angle at rear wheels ?r and a torque Mz. The method also includes obtaining an objective function based on a function of the vehicle dynamics x and the actuator dynamics u and formulating a cost function to minimize the objective function. The actuator dynamics u including the torque Mz are determined for a next time sample based on minimizing the objective function. The vehicle is controlled to implement the torque Mz.

Abstract: A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

Abstract: A method of controlling a vehicle includes obtaining a linear representation of a vehicle dynamics model that includes actuator dynamics u integrated with vehicle dynamics x. The actuator dynamics u include a road wheel angle at rear wheels ?r and a torque Mz. The method also includes obtaining an objective function based on a function of the vehicle dynamics x and the actuator dynamics u and formulating a cost function to minimize the objective function. The actuator dynamics u including the torque Mz are determined for a next time sample based on minimizing the objective function. The vehicle is controlled to implement the torque Mz.