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Real-time urban traffic information estimation with a limited number of surveillance cameras |
Guangtao XUE1( ), Ke ZHANG2, Qi HE1, Hongzi ZHU1 |
| 1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. Baidu Corporation, Shanghai 201203, China |
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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 measurementbased algorithm outperforms the traditional speed-based and model-based approaches by up to 50%.
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| Keywords
real-time traffic information
surveillance cameras
measurement-based traffic matrix estimation
topology pruning
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Corresponding Author(s):
XUE Guangtao,Email:gt_xue@sjtu.edu.cn
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Issue Date: 01 October 2012
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