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Real-time urban traffic information estimation with a limited number of surveillance cameras

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Abstract

Constant traffic congestion consumes enormous amounts of energy and causes vastly increased journey times. Therefore, real-time traffic information is of great importance to the public because such information is invaluable to more efficient traffic control and travel planning. To obtain such information in metropolises like Shanghai, however, is very challenging due to the extraordinarily large scale and complexity of the underlying road network. In this paper, we propose a novel traffic estimation scheme utilizing surveillance cameras pervasively deployed in cities. With only a limited number of roads with cameras, we adopt a measurementbased traffic matrix (TM) estimation method to infer the traffic conditions on those roads with no cameras. Extensively trace-driven simulations as well as field study results show that our scheme can achieve high accuracy with a very limited number of measurements. The accuracy of our measurement-based algorithm outperforms the traditional speed-based and model-based approaches by up to 50%.

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Correspondence to Guangtao Xue.

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Guangtao Xue received his PhD in Computer Science from Shanghai Jiao Tong University in 2004. He is an associate professor in the Department of Computer Science and Engineering at the Shanghai Jiao Tong University. His research interests include mobile networks, social networks, sensor networks, vehicular networks, and distributed computing. He is a member of the IEEE Computer Society and the Communication Society.

Ke Zhang received BS degree from Computer Science and Technology department of Finance and Economics of Jiangxi University in 2007. He received his MS degree in Computer Science from Shanghai Jiao Tong University in 2012. He is now a Browser-OS kernel developer in Baidu Corporation.

Qi He received his BS degree in Computer Science from Zhejiang University in 2009. He is currently a Master student at Shanghai Jiao Tong University under the supervision of Prof. Guangtao Xue. His research interests include data mining, social networking, delaytolerant networking, and cloud computing. Currently, his research mainly focuses on the improvement of wireless access point load balancing situation and data mining from user based 3G mobile networks.

Hongzi Zhu received his PhD in Computer Science from Shanghai Jiao Tong University in 2009. He is an assistant professor in the Department of Computer Science and Engineering at Shanghai Jiao Tong University. His research interests include mobile networks, vehicular networks, and network security. He is a member of the IEEE Computer Society and Communication Society.

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Xue, G., Zhang, K., He, Q. et al. Real-time urban traffic information estimation with a limited number of surveillance cameras. Front. Comput. Sci. 6, 547–559 (2012). https://doi.org/10.1007/s11704-012-2051-9

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  • DOI: https://doi.org/10.1007/s11704-012-2051-9

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