Home Journals Articles Updates About
CN
image
收藏切换
Cluster analysis of autonomous driving traffic accidents based on K-means and LCA
收藏切换
PDF
Jianfeng QIAO1, Yanan WANG1, Shuran LYU1, Ting WANG1, Xuefeng XIA2
China Safety Science Journal | 2025, 35(7) : 192 - 200
Less
收藏切换
China Safety Science Journal | 2025, 35(7): 192-200
• Public safety •
Cluster analysis of autonomous driving traffic accidents based on K-means and LCA
Full
Jianfeng QIAO1, Yanan WANG1, Shuran LYU1, Ting WANG1, Xuefeng XIA2
Affiliations
  • 1School of Management Engineering, Capital University of Economics and Business, Beijing 100070, China
  • 2International Branch, China Petroleum Corporation Logging Limited Company, Beijing 100101, China
Published: 2025-07-28 doi: 10.16265/j.cnki.issn1003-3033.2025.07.1025
Outline
收藏切换

To deeply explore the underlying patterns of road traffic accidents involving Autonomous Vehicles (AV), relying solely on the statistical analysis of individual accident description factors was insufficient. It was necessary to uncover further the comprehensive latent categories reflected by the interactions of multiple factors. Given that AV accident data contained structured information and narrative text, an innovative approach was proposed for type identification combining K-means clustering analysis and LCA. Specifically, the K-means method was used to extract key information from the narrative text, which was then fed into the LCA model to overcome the limitation of LCA being able to utilize only the structured information in existing accident reports. The effectiveness of this combined approach was verified using 437 AV traffic accidents in California, USA. The results show that AV accidents mainly manifest in four comprehensive types. The combined approach of K-means and LCA enables efficient clustering analysis of structured information that includes narrative text.

K-means  /  latent class analysis (LCA)  /  autonomous driving  /  cluster analysis  /  autonomous vehicles (AV)  /  traffic accidents
Jianfeng QIAO, Yanan WANG, Shuran LYU, Ting WANG, Xuefeng XIA. Cluster analysis of autonomous driving traffic accidents based on K-means and LCA[J]. China Safety Science Journal, 2025 , 35 (7) : 192 -200 . DOI: 10.16265/j.cnki.issn1003-3033.2025.07.1025
Appendix
Less
Year 2025 volume 35 Issue 7
PDF
89
9
Cite this Article
BibTeX
Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.07.1025
  • Receive Date：2025-03-04
  • Online Date：2026-07-09
  • Published：2025-07-28
Article Data
Affiliations
History
  • Received：2025-03-04
  • Revised：2025-05-09
Affiliations
    1School of Management Engineering, Capital University of Economics and Business, Beijing 100070, China
    2International Branch, China Petroleum Corporation Logging Limited Company, Beijing 100101, China
References
Share
https://castjournals.cast.org.cn/joweb/zgaqkxxb/EN/10.16265/j.cnki.issn1003-3033.2025.07.1025
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House