High-precision laser monitoring system with enhanced non-uniform scanning for railway safety
Abstract The intrusion of obstacles onto railway tracks presents a significant threat to train safety, characterized by sudden and unpredictable occurrences. With China leading the world in high-speed rail mileage, ensuring railway security is paramount. The current laser monitoring technologies suffer from high false alarm rates and unreliable intrusion identification. This study addresses these issues by investigating high-resolution laser monitoring technology for railway obstacles, focusing on key parameters such as monitoring range and resolution. We propose an enhanced non-uniform laser scanning method, developing a laser monitoring system that reduces the obstacle false alarm rate to 2.00%, significantly lower than the 20% standard (TJ/GW135-2015). This rate is the best record for laser monitoring systems on China Railway. Our system operates seamlessly in all weather conditions, providing superior accuracy, resolution, and identification efficiency. It is the only 3D LiDAR system certified by the China State Railway Group Co., Ltd. (Certificate No. [2023] 008). Over three years, our system has been deployed at numerous points along various lines managed by the China State Railway Group, accumulating a dataset of 300,000 observations. This extensive deployment has significantly enhanced railway safety. The development and implementation of our railway laser monitoring system represent a substantial advancement in railway safety technology. Its low false alarm rate (2.00%), high accuracy (20 cm × 20 cm × 20 cm), and robust performance in diverse conditions underscore its potential for widespread adoption, promising to enhance railway safety in China and internationally.
Authors
- Hongye Yan
- Weier Lu (ORCID: https://orcid.org/0000-0002-5163-9475)
- Xiaoqi Liu (ORCID: https://orcid.org/0000-0002-3317-4627)
- Cheng Wang (ORCID: https://orcid.org/0000-0001-6075-2878)
- Guotang Zhao
- Xuechun Lin (ORCID: https://orcid.org/0000-0002-4437-4958)
- Zhonglin Zhu
- Yingying Yang
- Yu Liu (ORCID: https://orcid.org/0009-0006-3110-8884)
Institutions
- Chinese Academy of Sciences (CN)
- Institute of Microelectronics (CN)
- China Railway Group (China) (CN)
- China Academy of Railway Sciences (CN)
- Institute of Semiconductors (CN)
- Southwest Jiaotong University (CN)
Publication Details
- Journal
- Railway Engineering Science
- Published
- 2024-08-23
- DOI
- https://doi.org/10.1007/s40534-024-00351-7
- Citations
- 5
- Primary Topic
- Advanced Optical Sensing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.53
Funders
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- Southwest Jiaotong University