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

Author:

Hussain Fizza,Ali YasirORCID,Li Yuefeng,Haque Md Mazharul

Publisher

Elsevier BV

Reference47 articles.

1. An extreme value theory approach to estimate crash risk during mandatory lane-changing in a connected environment;Ali;Anal. Methods Acc. Res.,2022

2. Predicting and explaining lane-changing behaviour using machine learning: a comparative study;Ali;Transp. Res. Part c: Emerg. Technol.,2022

3. Assessing traffic conflict/crash relationships with extreme value theory: Recent developments and future directions for connected and autonomous vehicle and highway safety research;Ali;Anal. Methods Acc. Res.,2023

4. A Bayesian generalised extreme value model to estimate real-time pedestrian crash risks at signalised intersections using artificial intelligence-based video analytics;Ali;Anal. Methods Acc. Res.,2023

5. Allen, B.L., Shin, B.T., Cooper, P.J., 1978. Analysis of traffic conflicts and collisions.

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