Urban congestion is a major and costly problem in many cities both in China and other countries. The purpose of building urban expressway is to alleviate the growing traffic pressure. In this paper, the mesoscopic traffic flow models are improved by variable speed limits strategy for the dynamic of vehicles on urban expressway network. The models include static queuing model, the velocity model, and the movement model of the vehicle. Moreover the method of the simulation is also proposed. So that we can get the corresponding variable speed limits values and aid traffic managers in making decisions to develop a network traffic flow control strategy. In the end, the elevated expressway of Jinan city is used as a simulation example. We investigated the performance of the transport system with averaged density, speed, and flow on link. We also analysed the dynamic of the traffic system on expressway network at different demand levels. The simulation results show that the models are feasible and effective and the variable speed limits strategy can successfully alleviate the traffic congestion in some extent. The operational efficiency of the transportation system is greatly improved.
As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.
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