Revisiting the hybrid approach of anomaly detection and extreme value theory for estimating pedestrian crashes using traffic conflicts obtained from artificial intelligence-based video analytics

Pedestrians represent a group of vulnerable road users who are at a higher risk of sustaining severe injuries than other road users. As such, proactively assessing pedestrian crash risks is of paramount importance. Recently, extreme value theory models have been employed for proactively assessing cr...

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Bibliographic Details

Main Authors:	Fizza Hussain, Yasir Ali, Yuefeng Li, Md Mazharul Haque
Format:	Default Article
Published:	2024
Subjects:	Transportation, logistics and supply chains Health sciences Public health Psychology Applied and developmental psychology Extreme value theory Machine learning Traffic conflics Anomaly detection Hybrid models Pedestrian safety
Online Access:	https://hdl.handle.net/2134/26087623.v1
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