NAVIGATION CONTROL IN AUTONOMOUS VEHICLES USING ARTIFICIAL INTELLIGENCE: A RECENT COMPREHENSIVE STRUCTURED REVIEW

Authors

  • Azuwir Mohd Nor Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohd Zakimi Zakaria Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohamad Ezral Baharudin Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Mohd Sazli Saad Faculty of Mechanical Engineering & Technology, Universiti Malaysia Perlis, Pauh Putra Campus, 02600 Arau, Perlis, Malaysia
  • Wan Sallha Yusoff Faculty of Business & Communication, Universiti Malaysia Perlis, Pusat Perniagaan Pengkalan Jaya, Jalan Alor Setar-Kangar, 01000 Kangar, Perlis, Malaysia
  • Muhammad Auzan Universitas Gadjah Mada, Bulaksumur, Yogyakarta 55281, Indonesia

DOI:

https://doi.org/10.11113/jurnalteknologi.v88.23773

Keywords:

Autonomous vehicles, neural networks, fuzzy logic, reinforcement learning, navigation control

Abstract

Navigation control plays a critical role in the performance and safety of autonomous vehicles, especially in dynamic and uncertain environments. Recent advances in artificial intelligence (AI) have led to the development of intelligent control strategies that improve lateral control, path tracking, and decision-making capabilities. The systematic review was performed with the PRISMA method in order both to comply with and evaluate alternatives. Through systematic searches in Scopus, Web of Science and IEEE databases a total of 30 primary studies were identified and reviewed, which fell under three broad themes: Reinforcement Learning and Fuzzy Logic Control Approaches; Neural Networks and AI Control Strategies; and Hybrid Control Strategies and Advanced Path Planning. The selected articles were then examined and discussed to evaluate their roles in improving the vehicle performance, stability and behaviour adaptivity. The findings indicate that AI based control navigation substantially increases the capabilities of autonomous vehicles, and more research will consequently refine those techniques for broad use.

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Published

2025-12-23

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Vol. 88 No. 1: January 2026

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Science and Engineering

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