Automated Traffic Safety Assessment Tool Utilizing Monocular 3D Convolutional Neural Network Based Detection Algorithm at Signalized Intersections-Reference-Cited by-同舟云学术

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Automated Traffic Safety Assessment Tool Utilizing Monocular 3D Convolutional Neural Network Based Detection Algorithm at Signalized Intersections

Published:2024-06-13 Issue: Volume:176 Page:456-467
ISSN:
Container-title:International Conference on Transportation and Development 2024
language:
Short-container-title:

Author:

Mohamed Ahmed¹¹¹,Li Lizhe¹¹¹,Ahmed Mohamed M.¹¹¹

Affiliation:

1. Dept. of Civil and Architectural Engineering and Construction Management, Univ. of Cincinnati, Cincinnati, OH.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784485514.040

Reference34 articles.

1. Using Closed-Circuit Television Cameras to Analyze Traffic Safety at Intersections Based on Vehicle Key Points Detection;Abdel-Aty M.;Accident Analysis and Prevention,2022

2. Incorporating Speed in a Traffic Conflict Severity Index to Estimate Left Turn Opposed Crashes at Signalized Intersections;Anarkooli A. J.;Transportation Research Record,2021

3. Automated Vehicle to Vehicle Conflict Analysis at Signalized Intersections by Camera and LiDAR Sensor Fusion;Anisha A. M.;Transportation Research Record: Journal of the Transportation Research Board,2022

4. Baer, R. 2005. Linear algebra and projective geometry. Courier Corporation.

5. Beymer, D., Mclauchlan, P., Coifman, B., and Malik, J. 1989. A Real-Time Computer Vision System for Measuring Traffic Parameters. https://doi.org/10.1109/CVPR.1997.609371.

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