A model‐based demand‐balancing control for dynamically divided multiple urban subnetworks |
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| Authors: | Shu Lin Qing‐Jie Kong Qingming Huang |
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| Affiliation: | 1. School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China;2. Key Lab of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing, China;3. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China |
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| Abstract: | Traffic control is an effective and efficient method for the problem of traffic congestion. It is necessary to design a high‐level controller to regulate the network traffic demands, because traffic congestion is not only caused by the improper management of the traffic network but also to a great extent caused by excessive network traffic demands. Therefore, we design a demand‐balance model predictive controller based on the macroscopic fundamental diagram‐based multi‐subnetwork model, which can optimize the network traffic mobility and the network traffic throughput by regulating the input traffic flows of the subnetworks. Because the transferring traffic flows among subnetworks are indirectly controlled and coordinated by the demand‐balance model predictive controller, the subnetwork division can variate dynamically according to real traffic states, and a global optimality can be achieved for the entire traffic network. The simulation results show the effectiveness of the proposed controller in improving the network traffic throughput. Copyright © 2016 John Wiley & Sons, Ltd. |
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| Keywords: | traffic network control urban road network macroscopic fundamental diagram traffic flow equilibrium |
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