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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Chu Thi Thuy
University of Economics-Technology for Industries
Computer Science & IT

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Model predictive control combined reinforcement learning for automatic vehicles applied in intelligent transportation system Vo Thanh Ha; Chu Thi Thuy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 2: April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i2.25274

Abstract

This paper presents the design of model predictive control (MPC) combined reinforcement learning (RL) applied in an intelligent transportation system (ITS). The car is to follow the reference path by the MPC control, and its parks in the parking by RL has been trained. The MPC controller constantly moves the vehicle along the reference path while the MPC algorithm searches for an empty parking spot. Meanwhile, the reinforcement learning-proximal policy optimization (RL-PPO) control will perform parking on demand if the MPC finds a parking position. This hybrid controller can quickly implement programming on MATLAB software by writing code. Furthermore, this hybrid controller simultaneously performs precise detection and avoidance of obstacles in tight parking spaces. The correctness of the theory is demonstrated through MATLAB/Simulink.
Co-Authors Vo Thanh Ha