Examining weekday-weekend variations in factors affecting pedestrian crashes: A geospatial explainable machine learning framework.

Wang Z, Fan W

DOI: 10.1016/j.aap.2026.108626
Published: 2026 Sep
Container: Accident; analysis and prevention
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.aap.2026.108626,
  title = {Examining weekday-weekend variations in factors affecting pedestrian crashes: A geospatial explainable machine learning framework.},
  author = {Wang Z and Fan W},
  year = {2026},
  journal = {Accident; analysis and prevention},
  doi = {10.1016/j.aap.2026.108626},
  url = {https://doi.org/10.1016/j.aap.2026.108626}
}

RIS

TY  - JOUR
TI  - Examining weekday-weekend variations in factors affecting pedestrian crashes: A geospatial explainable machine learning framework.
AU  - Wang Z
AU  - Fan W
PY  - 2026
JO  - Accident; analysis and prevention
DO  - 10.1016/j.aap.2026.108626
UR  - https://doi.org/10.1016/j.aap.2026.108626
ER  -

APA

Z, W., & W, F. (2026). Examining weekday-weekend variations in factors affecting pedestrian crashes: A geospatial explainable machine learning framework.. Accident; analysis and prevention. https://doi.org/10.1016/j.aap.2026.108626

Source records

pubmed · retrieved 2026-09-25T17:20:50.272Z