A data-driven approach to child pedestrian crash analysis using dimension reduction, clustering, and explainable AI

Swastika Barua, Rohit Chakraborty, Md. Monzurul Islam, Subasish Das

Open source

DOI: 10.1016/j.aap.2025.108229
Published: 2025-11
Container: Accident Analysis & Prevention
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.aap.2025.108229,
  title = {A data-driven approach to child pedestrian crash analysis using dimension reduction, clustering, and explainable AI},
  author = {Swastika Barua and Rohit Chakraborty and Md. Monzurul Islam and Subasish Das},
  year = {2025},
  journal = {Accident Analysis \&amp; Prevention},
  doi = {10.1016/j.aap.2025.108229},
  url = {https://doi.org/10.1016/j.aap.2025.108229}
}

RIS

TY  - JOUR
TI  - A data-driven approach to child pedestrian crash analysis using dimension reduction, clustering, and explainable AI
AU  - Swastika Barua
AU  - Rohit Chakraborty
AU  - Md. Monzurul Islam
AU  - Subasish Das
PY  - 2025
JO  - Accident Analysis &amp; Prevention
DO  - 10.1016/j.aap.2025.108229
UR  - https://doi.org/10.1016/j.aap.2025.108229
ER  -

APA

Barua, S., Chakraborty, R., Islam, M. M., & Das, S. (2025). A data-driven approach to child pedestrian crash analysis using dimension reduction, clustering, and explainable AI. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2025.108229

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crossref · retrieved 2026-09-25T20:58:19.274Z