Authors:
Akos Bokor
1
;
Adam Szabo
2
;
Szilard Aradi
2
and
Laszlo Palkovics
1
;
3
Affiliations:
1
Systems and Control Laboratory, HUN-REN Institute for Computer Science and Control (SZTAKI), Kende utca 13-17., H-1111 Budapest, Hungary
;
2
Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary
;
3
Sźechenyi István University, Egyetem tér 1., H-9026 Győr, Hungary
Keyword(s):
Autonomous Vehicles, Genetic Algorithm, Model-Based Control, Optimization.
Abstract:
This paper focuses on the design of lateral controllers for autonomous vehicles. To enhance passenger comfort while concurrently maintaining minimal deviation from the desired trajectory, the developed controllers are tuned by a Genetic Algorithm, whose cost function is following the ISO 2631 Standard. Three model-based controllers, a Linear Quadratic Regulator, a Linear Quadratic Servo algorithm, and a Model Predictive Controller have been compared in a simulation environment. The test case consists of a suburban road section, where the vehicles must successfully traverse at different velocities while minimizing the lateral acceleration and jerk affecting the passengers. To take into account the velocity-dependent dynamics of the system, the controllers are based on a Linear Parameter-Varying model of the system. The results show that the developed controllers meet the specified requirements regarding the equivalent acceleration, Motion Sickness Dose Value, and deviation from the de
sired trajectory.
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