IMM/EKF filter based classification of real-time freeway video traffic without learning-Reference-Cited by-同舟云学术

IMM/EKF filter based classification of real-time freeway video traffic without learning

Published:2021-04-12 Issue: Volume: Page:1-12
ISSN:1942-7867
Container-title:Transportation Letters
language:en
Short-container-title:Transportation Letters

Author:

Ouessai Asmâa¹^ORCID,Keche Mokhtar¹

Affiliation:

1. University of Sciences and Technology Mohamed Boudiaf (USTOMB), Faculty of Electrical Engineering, Department of Electronics, Signals and Images Laboratory, Bir El Djir- Oran, Algeria

Publisher

Informa UK Limited

Subject

Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/19427867.2021.1913304

Reference44 articles.

1. A Review of Traffic Congestion Prediction Using Artificial Intelligence

2. Bar-Shalom, Y., X. R. Li, and T. Kirubarajan. 2004. “Estimation with Applications to Tracking and Navigation: theory algorithms and software” by Y.Bar-Shalom, X. Rong Li, and T. Kirubarajan,453-458, Canada, John Wiley & Sons

3. Bertini, R. L., 2006. “You are the Traffic Jam: An Examination of Congestion Measures ”, In 85 th Annual Meeting of the Transportation Research Board 2006, pp. 17, Washington, D.C

4. Evolution of macroscopic models for modeling the heterogeneous traffic: an Indian perspective

5. A New Method of Constrained Optimization and a Comparison With Other Methods

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