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

Author:

Ali Yasir,Haque Md. Mazharul,Mannering Fred

Publisher

Elsevier BV

Subject

Safety Research,Transportation

Reference53 articles.

1. Comparing the usefulness of real-time driving aids in a connected environment during mandatory and discretionary lane-changing manoeuvres;Ali;Transportation Research Part C,2020

2. Cooperate or not? Exploring drivers’ interactions and response times to a lane-changing request in a connected environment;Ali;Transportation Research Part C,2020

3. Examining braking behaviour during failed lane-changing attempts in a simulated connected environment with driving aids;Ali;Transportation Research Part C,2022

4. Ali, Y., Haque, M., Washington, S., 2022b. A real-time crash risk estimation framework for signalized intersections. 8th International Road Safety Simulation Conference. Athens, Greece.

5. Connectivity’s impact on mandatory lane-changing behaviour: Evidences from a driving simulator study;Ali;Transportation Research Part C,2018

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