@inproceedings{438ebbca23ff4ff58a86e50bb76d1a41,
title = "A Method of Lane Departure Identification Based on Roadside Multi-Sensor Fusion",
abstract = "In order to reduce the lane departure accident caused by driver's negligence, lane departure warning systems (LDWS) have become increasingly prevalent and important. Most proposed approaches mainly focus on how to detect lane markings by single-vehicle systems. However, due to limited detection range and processing ability, the robustness of single-vehicle systems is poor in complex traffic scenarios. Therefore, this paper proposes a method of lane departure identification based on roadside multi-sensor fusion. The time to lane crossing (TLC) is used to identify the lane departure. Compared with a single-vehicle system, the roadside equipment has stronger robustness in special scenarios. This approach also avoids the calculation resource consumption of single-vehicle systems caused by lane detection. The experiment verified that the vehicle detection rate of various scenes exceeded 98\%, and the lane departure identification rate was 100\%.",
keywords = "Lane departure, Multi-sensor fusion, RSU",
author = "Pengfei Liu and Guizhen Yu and Bin Zhou and Da Li and Zhangyu Wang",
note = "Publisher Copyright: {\textcopyright} ASCE.; 20th COTA International Conference of Transportation Professionals: Advanced Transportation Technologies and Development-Enhancing Connections, CICTP 2020 ; Conference date: 14-08-2020 Through 16-08-2020",
year = "2020",
doi = "10.1061/9780784482933.017",
language = "英语",
series = "CICTP 2020: Advanced Transportation Technologies and Development-Enhancing Connections - Proceedings of the 20th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "190--201",
editor = "Haizhong Wang and Heng Wei and Lei Zhang and Yisheng An",
booktitle = "CICTP 2020",
address = "美国",
}