Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach-Reference-Cited by-同舟云学术

Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach

Published:2024-02-27 Issue:1 Volume:22 Page:216-228
ISSN:1348-8503
Container-title:International Journal of Intelligent Transportation Systems Research
language:en
Short-container-title:Int. J. ITS Res.

Author:

Avval Seyed Soroush Tabadkani,Eghbal Najmeh

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s13177-024-00391-7.pdf

Reference22 articles.

1. Tedjopurnomo, D.A., et al.: A survey on modern deep neural network for traffic prediction: Trends, methods and challenges. IEEE Trans. Knowl. Data Eng. 34(4), 1544–1561 (2020)

2. Haydari, A., Yılmaz, Y.: Deep reinforcement learning for intelligent transportation systems: A survey. IEEE Trans. Intell. Transp. Syst. 23(1), 11–32 (2020)

3. van de Weg, G.S., et al.: Efficient freeway MPC by parameterization of ALINEA and a speed-limited area. IEEE Transactions on Intelligent Transportation Systems 20(1), 16–29 (2018)

4. Guo, Q., Li, L., Xuegang, J.B.: Urban traffic signal control with connected and automated vehicles: A survey. Transportation research part C: emerging technologies 101, 313–334 (2019)

5. Papamichail, I., et al.: Coordinated ramp metering for freeway networks–a model-predictive hierarchical control approach. Transportation Research Part C: Emerging Technologies 18(3), 311–331 (2010)

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1. Correction to: Model Predictive Sliding Mode Control of Highway Traffic Flow: Cooperative and Integrated Approach;International Journal of Intelligent Transportation Systems Research;2024-06-18