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Lane Keeping Human-Machine Co-Driving Strategy Considering Drivers’ Lateral Driving Habits
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Ping Liu1, 2, Yunpeng Tian1, 2, Haotian Duan1, 2, Jiayu Yao1, 2
Automobile Technology | 2025, (4) : 1 - 9
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Automobile Technology | 2025, (4): 1-9
Lane Keeping Human-Machine Co-Driving Strategy Considering Drivers’ Lateral Driving Habits
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Ping Liu1, 2, Yunpeng Tian1, 2, Haotian Duan1, 2, Jiayu Yao1, 2
Affiliations
  • 1 School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031
  • 2 Engineering Research Center of Advanced Drive Energy Saving Technology, Ministry of Education, Southwest Jiaotong University, Chengdu 610031
Published: 2025-04-24 doi: 10.19620/j.cnki.1000-3703.20231128
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In order to address the issue of human-machine conflict caused by the neglect of human-machine interaction in traditional lane keeping assistance systems, this paper proposes a lane keeping human-machine co-driving strategy. A lane departure decision model considering the drivers’ lateral driving habits is designed by characterizing the drivers’ lateral driving habits based on their historical lateral positions and dynamically dividing the road boundary according to 3σ principles. At the same time, the control of the assisted driving system is allocated based on the risk assessment value and driver fatigue factor. The experimental results show that the proposed human-machine co-driving strategy can effectively avoid lane departure risks caused by fatigue driving and driving errors. The lane keeping assistance systems, which considers the lateral driving habits of drivers can provide drivers with sufficient freedom while applying appropriate constraints to suppress lane departure, effectively reducing human-machine conflicts and ensuring safety.

Human machine shared driving  /  Lane departure decision model  /  Lane keep assist system  /  Lateral driving  /  Human-machine conflict
Ping Liu, Yunpeng Tian, Haotian Duan, Jiayu Yao. Lane Keeping Human-Machine Co-Driving Strategy Considering Drivers’ Lateral Driving Habits[J]. Automobile Technology, 2025 , (4) : 1 -9 . DOI: 10.19620/j.cnki.1000-3703.20231128
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doi: 10.19620/j.cnki.1000-3703.20231128
  • Online Date：2025-11-15
  • Published：2025-04-24
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  • Revised：2024-02-20
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    1 School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031
    2 Engineering Research Center of Advanced Drive Energy Saving Technology, Ministry of Education, Southwest Jiaotong University, Chengdu 610031
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