Safety has being a concern as a result of the high rate of road accidents and has led to the development of driver assistance system such as Active braking, Cruise Control, Lane departure warning lane keeping and etc. has become a very active research area. However, this paper presents the performance and robustness analysis of a model predictive control and proportional integral derivative control for lane keeping maneuvers of an autonomous vehicle using computer vision simulation studies. A simulation study was carried out where a vehicle model based on single tracked bicycle model was developed in MATLAB/SIMULINK environment together with a vision dynamic system. Both PID controller and MPC were simulated to maintain the desired reference trajectory of the vehicle by controlling steering angle. Further performance and robustness analysis were carried out and the simulation results show that the proposed control system for the PID control achieved its objective even though it was less robust in maintaining its performance under various conditions like vehicle load change, different longitudinal speed and different cornering stiffness. While in the case of MPC the optimizer made sure that the predicted future trajectory of the vehicle output tracks the desired reference trajectory and was more robust in maintaining its performance under same conditions as in PID.
Lane Keeping Maneuvers Using Proportional Integral Derivative (PID) and Model Predictive Control (MPC)
2021-03-19
doi:10.18196/jrc.2256
Journal of Robotics and Control (JRC); Vol 2, No 2 (2021): March; 78-82 ; 2715-5072 ; 2715-5056
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC: | 629 |
Autonomous Lane Change Control Using Proportional-Integral-Derivative Controller and Bicycle Model
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