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<p>The evolution of lane-keeping assistance systems (LKAS) has significantly contributed to enhancing road safety, driving comfort, and reducing driver workload. The automotive sector is moving towards a safer driving experience with autonomous agricultural vehicles in the field. The article intends to design and develop a system capable of detecting agricultural lanes and giving appropriate steering control outputs. The research aim is to build a system of Level-2 autonomous agricultural vehicle facilities for advanced driver assistance systems, and allow the driver to assist the vehicle in the left and right lane turns. The experimental model uses image processing to detect lanes on roads. The experimental results show that the LKAS model output is derived from an entry speed of 30&#xa0;km/h to 60&#xa0;km/h, a controller with a prediction horizon of 1.75&#xa0;s to 2.5&#xa0;s, and a control horizon of 0.5 to 0.75&#xa0;s on a 3&#xa0;km straight test track. The proposed approach has a 14% better performance in terms of execution time for steering inputs applied by the driver.</p>

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Development and integration of control strategy for level-2 autonomous vehicle lane-keeping assist system

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月5日

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  • Roushan Kumar,
  • Adesh Kumar,
  • Jitendra Yadav,
  • Chaman Verma,
  • Zoltán Illés,
  • Deepak Kumar

摘要

The evolution of lane-keeping assistance systems (LKAS) has significantly contributed to enhancing road safety, driving comfort, and reducing driver workload. The automotive sector is moving towards a safer driving experience with autonomous agricultural vehicles in the field. The article intends to design and develop a system capable of detecting agricultural lanes and giving appropriate steering control outputs. The research aim is to build a system of Level-2 autonomous agricultural vehicle facilities for advanced driver assistance systems, and allow the driver to assist the vehicle in the left and right lane turns. The experimental model uses image processing to detect lanes on roads. The experimental results show that the LKAS model output is derived from an entry speed of 30 km/h to 60 km/h, a controller with a prediction horizon of 1.75 s to 2.5 s, and a control horizon of 0.5 to 0.75 s on a 3 km straight test track. The proposed approach has a 14% better performance in terms of execution time for steering inputs applied by the driver.