This paper presents a controller dedicated to the lateral and longitudinal vehicle dynamics control for autonomous driving. The proposed strategy exploits a Model Predictive Control strategy to perform lateral guidance and speed regulation. To this end, the algorithm controls the steering angle and the throttle and brake pedals for minimizing the vehicle’s lateral deviation and relative yaw angle with respect to the reference trajectory, while the vehicle speed is controlled to drive at the maximum acceptable longitudinal speed considering the adherence and legal speed limits. The technique exploits data computed by a simulated camera mounted on the top of the vehicle while moving in different driving scenarios. The longitudinal control strategy is based on a reference speed generator, which computes the maximum speed considering the road geometry and lateral motion of the vehicle at the same time. The proposed controller is tested in highway, interurban and urban driving scenarios to check the performance of the proposed method in different driving environments.
A Model Predictive Control Strategy for Lateral and Longitudinal Dynamics in Autonomous Driving / Khan, Irfan; Feraco, Stefano; Bonfitto, Angelo; Amati, Nicola. - ELETTRONICO. - 4:(2020). (Intervento presentato al convegno ASME - 22nd International Conference on Advanced Vehicle Technologies (AVT) tenutosi a Virtual nel 17-19/08/2020) [10.1115/DETC2020-22287].
A Model Predictive Control Strategy for Lateral and Longitudinal Dynamics in Autonomous Driving
Khan, Irfan;Feraco, Stefano;Bonfitto, Angelo;Amati, Nicola
2020
Abstract
This paper presents a controller dedicated to the lateral and longitudinal vehicle dynamics control for autonomous driving. The proposed strategy exploits a Model Predictive Control strategy to perform lateral guidance and speed regulation. To this end, the algorithm controls the steering angle and the throttle and brake pedals for minimizing the vehicle’s lateral deviation and relative yaw angle with respect to the reference trajectory, while the vehicle speed is controlled to drive at the maximum acceptable longitudinal speed considering the adherence and legal speed limits. The technique exploits data computed by a simulated camera mounted on the top of the vehicle while moving in different driving scenarios. The longitudinal control strategy is based on a reference speed generator, which computes the maximum speed considering the road geometry and lateral motion of the vehicle at the same time. The proposed controller is tested in highway, interurban and urban driving scenarios to check the performance of the proposed method in different driving environments.File | Dimensione | Formato | |
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IDETC2020-22287-A Model Predictive Control Strategy For Lateral And Longitudinal Dynamics In Autonomous Driving.pdf
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https://hdl.handle.net/11583/2851449