Abstract: Systems and methods are provided for uncertainty based contingency model predictive control of a vehicle in uncertain road conditions. Applications may be found for collision imminent steering, on-road autonomous vehicles and real time decision-making influenced by an unknown environment. An uncertainty road coefficient of friction may be estimated using an Unscented Kalman filter, and the controller may be updated based upon the estimated uncertainties to provide for collision avoidance in unknown conditions.

Abstract: A method in a data processing system including at least one processor and at least one memory including instructions executed by the at least one processor to implement a lane change system is provided by the present disclosure. The method includes receiving, from at least one of a plurality of sensors coupled to a vehicle, information associated with a location of an object longitudinally ahead of the vehicle, determining a sequence of control inputs associated with a time horizon to avoid a collision between the vehicle and the object based on a constraint and the location of the object, and the determining the sequence of control inputs including minimizing a maximum tire slip angle of the vehicle during the time horizon subject to the constraint, and causing a vehicle control system of the vehicle to perform a vehicle maneuver based on the sequence of control inputs.