Text Extraction and Correlation Analysis of Multi-Factor Mechanisms Influencing Traffic Accident Severity in Expressway Reconstruction and Expansion Projects

DOI

10.2991/978-94-6463-610-9_32How to use a DOI?

Keywords

traffic engineering; natural language processing; weighted correlation rules; expressway reconstruction and expansion; traffic accident severity; traffic accident causation

Abstract

To accurately extract key factors from unstructured traffic accident texts and identify the interaction mechanisms among factors affecting the severity of accidents during such projects, a combined deep learning model based on BERT-BiLSTM-CRF-WApriori model is proposed. It blends Bi-directional Encoder Representation from Transformers (BERT), Bi-directional Long Short-Term Memory (BiLSTM), Conditional Random Field (CRF), and weighted Apriori association rule algorithm (WApriori),Using the BERT-BiLSTM-CRF-WApriori model, complex accident factors—including road factors, traffic factors, construction factors, environmental factors, driver factors and other complex factors in expressway reconstruction and expansion, are extracted from unstructured traffic accident texts related to expressway reconstruction and expansion projects, facilitating the analysis of interaction mechanisms influencing accident severity. The results show that the severity of sideswipe accidents in construction areas is relatively low, over speed vehicles in the lane closed construction area and involving truck will increase the severity of the accident; collisions between truck and fixture crash or intruding into the work area are likely to cause serious accidents. These research results can inform targeted measures for controlling traffic accidents and reducing injuries during expressway reconstruction and expansion project.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jingshi Li
AU  - Zhongguang Wu
AU  - Zechao Huang
AU  - Jiatian Hao
AU  - Yuanbo Zhang
AU  - Ying Li
PY  - 2024
DA  - 2024/12/16
TI  - Text Extraction and Correlation Analysis of Multi-Factor Mechanisms Influencing Traffic Accident Severity in Expressway Reconstruction and Expansion Projects
BT  - Proceedings of the 2024 International Conference on Rail Transit and Transportation (ICRTT 2024)
PB  - Atlantis Press
SP  - 286
EP  - 297
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-610-9_32
DO  - 10.2991/978-94-6463-610-9_32
ID  - Li2024
ER  -