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Effects of Roll Dynamics in Model Predictive Control for Autonomous Vehicles

Paolo Falcone (Institutionen för signaler och system, Mekatronik) ; Giovanni Palmieri ; H. Eric Tseng ; Luigi Glielmo
47th IEEE Conference on Decision and Control, December 9-11, 2008, Fiesta Americana Grand Coral Beach, Cancun, Mexico (2008)
[Konferensbidrag, refereegranskat]

A Model Predictive Control (MPC) approach for autonomous vehicles is presented. We formulate a predictive control problem in order to best follow a given path by controlling the front steering angle. We start from the results presented in [4] and [7], where the MPC problem formulation relies on a simple bicycle model, and reformulate the problem by using a more complex vehicle model including roll dynamics. We present and discuss simulations of a vehicle performing high speed double lane change maneuvers where roll dynamics become relevant. The results demonstrate that the proposed model based design is able to effectively stabilize the vehicle by using a three dimensional vehicle model at the cost of a higher computational load.

Denna post skapades 2008-07-23. Senast ändrad 2017-06-28.
CPL Pubid: 72525


Institutioner (Chalmers)

Institutionen för signaler och system, Mekatronik (2005-2017)


Optimeringslära, systemteori

Chalmers infrastruktur