Abstract: 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.

Abstract: 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.

Abstract: Methods and systems are provided for controlling an autonomous vehicle. In one embodiment, a method includes: A method of controlling an autonomous vehicle, comprising: receiving, by a processor, a first set of data obtained from an inertial measurement unit of the vehicle; receiving, by the processor, a second set of data obtained from a global positioning system of the vehicle; receiving, by the processor, a third set of data obtained from a camera of the vehicle; determining, by the processor, at least two vehicle states relative to markings of a lane by processing the first set of data, the second set of data, and the third set of data as measurement with an extended Kalman filter; and controlling, by the processor, the vehicle based on the at least two vehicle states.