A Bayesian extreme value theory modelling framework to assess corridor-wide pedestrian safety using autonomous vehicle sensor data
- DOI
- 10.1016/j.aap.2023.107416
- Published
- 2024-02
- Container
- Accident Analysis & Prevention
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.aap.2023.107416,
title = {A Bayesian extreme value theory modelling framework to assess corridor-wide pedestrian safety using autonomous vehicle sensor data},
author = {Sunny Singh and Yasir Ali and Md Mazharul Haque},
year = {2024},
journal = {Accident Analysis \& Prevention},
doi = {10.1016/j.aap.2023.107416},
url = {https://doi.org/10.1016/j.aap.2023.107416}
}RIS
TY - JOUR TI - A Bayesian extreme value theory modelling framework to assess corridor-wide pedestrian safety using autonomous vehicle sensor data AU - Sunny Singh AU - Yasir Ali AU - Md Mazharul Haque PY - 2024 JO - Accident Analysis & Prevention DO - 10.1016/j.aap.2023.107416 UR - https://doi.org/10.1016/j.aap.2023.107416 ER -
APA
Singh, S., Ali, Y., & Haque, M. M. (2024). A Bayesian extreme value theory modelling framework to assess corridor-wide pedestrian safety using autonomous vehicle sensor data. Accident Analysis & Prevention. https://doi.org/10.1016/j.aap.2023.107416
Source records
- crossref · retrieved 2026-09-25T15:47:26.249Z