Safety-oriented and explainable machine learning for KSI crash risk prediction: Evidence from the United Kingdom

Khanh Giang Le

doi:10.1371/journal.pone.0347873

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Open Access

Peer-reviewed

Research Article

Safety-oriented and explainable machine learning for KSI crash risk prediction: Evidence from the United Kingdom

Khanh Giang Le

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: gianglk@utc.edu.vn

Affiliation Faculty of Civil Engineering, University of Transport and Communications, Hanoi, Vietnam

https://orcid.org/0000-0002-6295-8578

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Safety-oriented and explainable machine learning for KSI crash risk prediction: Evidence from the United Kingdom

Khanh Giang Le

Published: April 28, 2026
https://doi.org/10.1371/journal.pone.0347873

About the Authors

Khanh Giang Le

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: gianglk@utc.edu.vn

Affiliation Faculty of Civil Engineering, University of Transport and Communications, Hanoi, Vietnam

https://orcid.org/0000-0002-6295-8578

Competing Interests

The authors have declared that no competing interests exist.

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Medical risk factors
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Machine learning
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Traffic safety
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Roads
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Machine learning algorithms
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Meteorology
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Decision making
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Optimization
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