A Bayesian generalised extreme value model to estimate real-time pedestrian crash risks at signalised intersections using artificial intelligence-based video analytics

Pedestrians represent a vulnerable road user group at signalised intersections. As such, properly estimating pedestrian crash risk at discrete short intervals is important for real-time safety management. This study proposes a novel real-time vehicle-pedestrian crash risk modelling framework for sig...

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Bibliographic Details

Main Authors:	Yasir Ali, Md. Mazharul Haque, Fred Mannering
Format:	Default Article
Published:	2022
Subjects:	Civil engineering Civil engineering not elsewhere classified Pedestrian safety Real-time Crash risk Bayesian model Signal cycle Signalised intersection Science & Technology Life Sciences & Biomedicine Technology Public, Environmental & Occupational Health Transportation
Online Access:	https://hdl.handle.net/2134/22086296.v1
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