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All Journal International Journal of Artificial Intelligence and Robotics (IJAIR)
Bambang Lelono Widjiantoro
jpte@ejournal.unesa.ac.id
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Design of Predictive Control System for Lane Change in Autonomous Vehicle Mega Permatasari, Shervind Maharani; Widjiantoro, Bambang Lelono; Indriawati, Katherin
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 6 No. 1 (2024): May 2024
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v6i1.8141

Abstract

The automobile business is introducing a lot of autonomous vehicles in the modern day. Lane changes are one of the most complicated urban scenarios in which autonomous vehicles are used. Self-driving automobiles must thus interact with human-driven vehicles in a certain way. In this work, we concentrate on the autonomous vehicle's lane-changing control system for obstacle avoidance. This study employs a predictive control system as its methodology. The vehicle's next movements can be predicted by this control system. The vehicle's position, which is adjusted by the steering angle, is the controllable variable. The vehicle's position, which is adjusted by the steering angle, is the controllable variable. It is clear from the numerical simulation results that the predictive control system executes control actions on lane changes correctly, avoiding collisions with the running vehicle obstacles. RMSE (Root-Mean Square Error) is a performance metric that is derived from the difference between the vehicle's lateral position and the reference trajectory value. The RMSE of the planned predictive control is 0.9681.
Co-Authors Katherin Indriawati Mega Permatasari, Shervind Maharani