Modeling and simulating traffic congestion propagation in connected vehicles driven by temporal and spatial preference-Reference-Cited by-同舟云学术

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Modeling and simulating traffic congestion propagation in connected vehicles driven by temporal and spatial preference

Published:2015-07-21 Issue:4 Volume:22 Page:1121-1131
ISSN:1022-0038
Container-title:Wireless Networks
language:en
Short-container-title:Wireless Netw

Author:

Liu Zhao,Liu Yanheng,Wang Jian,Deng Weiwen

Funder

National Nature Science Foundation

Jilin Provincial International Cooperation Foundation

Scientific Research Foundation for Returned Scholars

ISEF program of KFAS

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Link

http://link.springer.com/content/pdf/10.1007/s11276-015-1021-1.pdf

Reference48 articles.

1. Ghazy, A., & Ozkul, T. (2009). Design and simulation of an artificially intelligent vanet for solving traffic congestion. In Proceedings of the IEEE international symposium on mechatronics and its applications, pp. 1–6.

2. Busch, C., Kannan, R., & Vasilakos, A. V. (2012). Approximating congestion+ dilation in networks via “quality of routing” games. IEEE Transactions on Computers, 61(9), 1270–1283.

3. Tian, D., Zhou, J., Wang, Y., Zhang, G., & Xia, H. (2015). An adaptive vehicular epidemic routing method based on attractor selection model. Ad Hoc Networks. doi: 10.1016/j.adhoc.2015.05.018 .

4. Wang, X., Vasilakos, A. V., Chen, M., Liu, Y., & Kwon, T. T. (2012). A survey of green mobile networks: Opportunities and challenges. Mobile Networks and Applications, 17(1), 4–20.

5. Attar, A., Tang, H., Vasilakos, A. V., Yu, F. R., & Leung, V. (2012). A survey of security challenges in cognitive radio networks: Solutions and future research directions. Proceedings of the IEEE, 100(12), 3172–3186.

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