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Before-after safety evaluation of part-time protected right-turn signals: An extreme value theory approach by applying artificial intelligence-based video analytics

Howlader, Md Mohasin ; Ali, Yasir ; Burbridge, Andrew ; Haque, Md Mazharul

Accident analysis and prevention, 2024-01, Vol.194, p.107341-107341, Article 107341 [Periódico revisado por pares]

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  • Título:
    Before-after safety evaluation of part-time protected right-turn signals: An extreme value theory approach by applying artificial intelligence-based video analytics
  • Autor: Howlader, Md Mohasin ; Ali, Yasir ; Burbridge, Andrew ; Haque, Md Mazharul
  • É parte de: Accident analysis and prevention, 2024-01, Vol.194, p.107341-107341, Article 107341
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
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  • Descrição: Extreme value theory models have opened doors for before-after safety evaluation of engineering treatments using traffic conflict techniques. Recent advancements in automated conflict extraction technologies have further expedited conflict-based safety evaluation as a potential alternative to traditional crash-based methods. However, the suitability of extreme value theory models in the before-after evaluation of engineering treatments needs to be rigorously tested. As such, this study proposes a traffic conflict-based before-after evaluation of a novel part-time protected right-turn signal strategy for right-turn or opposing-through crashes at signalised intersections. A part-time protected right-turn signal strategy refers to a signal arrangement where permissive and fully protected right-turn phasings are operated during peak and off-peak hours, respectively. A deep neural network-based computer vision technique was applied to extract the conflicts from a total of 654 h of video recordings (before period: 266 h and after period: 388 h) over seven treated approaches, and four matching control approaches at five signalised intersections in the city of Cairns, Australia. Using post encroachment time and post-collision velocity difference as traffic conflict measures, non-stationary bivariate generalised extreme value models were developed to estimate the severe and non-severe opposing-through crashes at signal cycle levels. The odds ratio analysis of model-predicted crash risks suggests that part-time protected right-turn signals reduce 67% and 81% of severe and non-severe opposing-through crashes at signalised intersections, respectively. Part-time protected right-turn signal strategy offers a good safety solution without precipitating need for capacity upgrades to accommodate queued right turners at signalised intersections.
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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