Irfan Khan
Combined lateral and longitudinal control for autonomous driving based on Model Predictive Control.
Rel. Nicola Amati, Andrea Tonoli, Angelo Bonfitto. Politecnico di Torino, Corso di laurea magistrale in Automotive Engineering (Ingegneria Dell'Autoveicolo), 2019
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Abstract
Autonomous ground vehicles, as an important part of intelligent transportation system, are attracting more attention than ever before. Their control system usually consists of three modules: environment perception, planning and decision-making, and vehicle control. Vehicle control is one of the most critical part of the whole architecture, as it is responsible for the vehicle guidance considering both safety and comfort. In general, control can be divided into lateral control and longitudinal velocity control. Their inter coordination leads to autonomous vehicle motion. This thesis is focused on the development of a combined lateral and longitudinal controller for autonomous driving based on Model Predictive Control (MPC).
The proposed strategy utilizes an adaptive MPC to perform lateral guidance and speed regulation by acting on the steering angle and acceleration/deceleration to minimize the vehicle’s lateral deviation and relative yaw angle with respect to the reference trajectory, while driving the vehicle at the maximum acceptable longitudinal speed
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