Vision-Based Lane Departure Warning Systems: Algorithms, Empirical Effectiveness, and Pathways to Enhanced Driving Safety

Vision-Based Lane Departure Warning Systems: Algorithms, Empirical Effectiveness, and Pathways to Enhanced Driving Safety

Authors

  • Ruixuan Li Guangzhou Huafeng Senior Technical School, 510800

DOI:

https://doi.org/10.66069/ojspub.26820705

Keywords:

Vision, Lane departure warning system, Image processing, Algorithm design, System implementation

Abstract

This study presents a vision‑based lane departure warning system, detailing its fundamental principles and system architecture. Lane markings are identified via advanced image processing, and algorithms are designed to determine vehicle deviation. Through systematic testing and optimization, the system achieves timely and accurate alerts, effectively mitigating accident risks associated with lane departure and demonstrating substantial practical value.

References

Zhong Yong. Research on Lane Line Detection and Vehicle Departure Warning Method Based on Machine Vision [D]. Jiangxi University of Science and Technology, 2023.

Yi Qi. Research and Design of Vehicle Rainy Day Lane Departure Warning System Based on Android [D]. Wuhan University of Science and Technology, 2023.

Wu Tong. Research on Lane Line Detection and Departure Warning System Based on Machine Vision [D]. Taiyuan University of Technology, 2022.

Chen Huaqing. Vehicle Recognition of Auxiliary Driving System Based on Lane Departure Warning [D]. Liaoning University of Technology, 2021.

Yang Fangyuan. Research on Control Optimization of Automobile Lane Departure Warning System [D]. Chongqing Jiaotong University, 2021.

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Published

2026-07-31

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Section

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