Multi-Agent Reinforcement Learning Control for Ramp Metering-Reference-Cited by-同舟云学术

Multi-Agent Reinforcement Learning Control for Ramp Metering

Published:2015 Issue: Volume: Page:167-173
ISSN:2194-5357
Container-title:Progress in Systems Engineering
language:
Short-container-title:

Author:

Fares Ahmed,Gomaa Walid

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-08422-0_25

Reference19 articles.

1. Yu, X., Xu, W., Alam, F., Potgieter, J., Fang, C.: Genetic fuzzy logic approach to local ramp metering control using microscopic traffic simulation. In: Mechatronics and Machine Vision in Practice (M2VIP), 2012 19th International Conference. (2012) 290–297

2. Ghods, A., Kian, A., Tabibi, M.: Adaptive freeway ramp metering and variable speed limit control: a genetic-fuzzy approach. Intelligent Transportation Systems Magazine, IEEE 1(1) (2009) 27–36

3. Liang, X., Li, J., Luo, N.: Single neuron based freeway traffic density control via ramp metering. In: Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on. (2010) 1–4

4. Li, J., Liang, X.: Freeway ramp control based on single neuron. In: Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on. Volume 2. (2009) 122–125

5. Feng, C., Yuanhua, J., Jian, L., Huixin, Y., Zhonghai, N.: Design of fuzzy neural network control method for ramp metering. In: Measuring Technology and Mechatronics Automation (ICMTMA), 2011 Third International Conference on. Volume 1. (2011) 966–969

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