Model Predictive Control for Road Disturbance Rejection in On-Curb Parking Scenarios

While there is still a long way to robustly operating fully automated vehicles on our roads, low speed autonomy might be a reasonable intermediate step. Especially highly automated parking systems are currently in the focus of interest. When we aim at leveraging those systems in everyday parking scenarios, we should also be able to park on sidewalks and as such be able to traverse curbs. However, those use cases might then be a major challenge for vehicle control systems. Therefore, this paper describes the design of a control scheme for longitudinal vehicle dynamics control which is capable of performing on-curb parking while lateral vehicle dynamics control is assumed to be performed by a separate controller. We rely on a model predictive control scheme which exploits information of an extended Kalman filter for the purpose of disturbance rejection when parking on curbs. The estimator aims at determining the related road resistance forces in those scenarios. The proposed control concept is compared to a proportional-integral controller in five typical parking scenarios. Simulation results demonstrate that with predictive control, we are able to finish parking faster, to avoid unintended stops and to better track the reference velocity.