Computer Vision for Traffic Monitoring

Thompson, Matthew; Lowry, Michael; Abdel-Rahim, Ahmed

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Computer Vision for Traffic Monitoring

2024-05-01
By Thompson, Matthew ; Lowry, Michael ; Abdel-Rahim, Ahmed

File Language:

English

Details

Creators:

Thompson, Matthew ; Lowry, Michael ; Abdel-Rahim, Ahmed
Corporate Creators:

University of Idaho ; Pacific Northwest Transportation Consortium (PacTrans) (UTC)
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

2022-S-UI-3
Resource Type:

Tech Report
Geographical Coverage:

United States;Washington
Edition:

Final Report 08/15/2023 – 05/31/2024
Corporate Publisher:

Pacific Northwest Transportation Consortium (PacTrans) (UTC)
Abstract:

This project examined computer vision applications for traffic monitoring and safety analysis. The focus was on evaluating the open-source computer vision code that we developed. Three case studies were completed using our computer vision code. The code was written in Python and uses a detection model called YOLOv8. The first case study demonstrated how user counts can be obtained from video feeds and provided examples of insights that can be drawn from these counts. The second case study used computer vision to create visualizations of user movements at intersections. The third case study developed and demonstrated the application of a new surrogate safety measure for pedestrian and bicyclist safety. Shortcomings and future opportunities of open-source computer vision systems are discussed.
Format:

PDF
Funding:

69A3551747110
Download URL:

https://rosap.ntl.bts.gov/view/dot/79662/dot_79662_DS1.pdf
File Type:

[PDF - 2.25 MB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:835c8b20eff8f197a655463fb9c3459052fb139f74d1117aa20ec8208575865459ab5c61b4eccf8087faf64d9358940e83921fdf73cab83e95518d87a0698beb

File Language:

English

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