Autonomous vehicle path following system design using a combined control approach

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Sevim B., EMİRLER M. T.

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2026 (SCI-Expanded, Scopus)

• Yayın Türü: Makale / Tam Makale
• Basım Tarihi: 2026
• Doi Numarası: 10.1177/09544070261441919
• Dergi Adı: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
• Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
• Anahtar Kelimeler: autonomous vehicles, control system design, LQI, path following, pure pursuit, reinforcement learning with PSO
• Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Autonomous vehicles represent a central component of future automotive technologies. One of the critical challenges in enabling this technology is the development of path following control systems. This study presents a linear quadratic integral (LQI) optimal control approach improved by particle swarm optimization (PSO), reinforcement learning particle swarm optimization policy (PSO-P), and pure pursuit (PP) for the design of a control system for autonomous vehicle path following. A novel combined control system is proposed by integrating LQI, PSO-P, and PP methods. To further enhance system performance, a feed-forward steering control system is incorporated into all control strategies. The proposed and benchmark control systems are evaluated and compared using time-domain simulations in the MATLAB/Simulink and IPG CarMaker co-simulation environment. Statistical analyses were performed using performance metrics and data from two distinct path curvatures. The results demonstrated the efficacy of the method compared to alternative control strategies.