Abstract
The volume of passenger flow in urban rail transit network operation continues to increase. Effective measures of passenger flow control can greatly alleviate the pressure of transportation and ensure the safe operation of urban rail transit systems. The controllability of an urban rail transit passenger flow network determines the equilibrium state of passenger flow density in time and space. First, a passenger flow network model of urban rail transit and an evaluation index of the alternative set of flow control stations are proposed. Then, the controllable determination model of the urban rail transit passenger flow network is formed by converting the passenger flow distribution into a system state equation based on system control theory. The optimization method of passenger flow control stations is established via driver node matching to realize the optimized control of network stations. Finally, a real-world case study of the Beijing subway network is presented to demonstrate that the passenger flow network is controllable when driver nodes compose 25.3% of the entire network. The optimization of the flow control station, set during the morning peak, proves the efficiency and validity of the proposed model and algorithm.
Highlights
Due to their large size, fast speed, and safety, urban rail transit systems have become the backbone of city transportation
This paper proposed an optimization method for flow control of urban rail transit based on the state-space equation and the driver node-matching algorithm
(1) The analysis of the characteristics of the complex network based on the passenger flow indicated that the passenger flow of the Beijing urban rail transit network has a “scale-free” characteristic
Summary
Due to their large size, fast speed, and safety, urban rail transit systems have become the backbone of city transportation. With network integration of urban rail transit, traditional passenger flow control methods cannot accommodate the increasingly large-volume, line-intensive, complex organizational conditions in modern transit systems. The strategy of flow control optimization for urban rail transit network controllability provides a new perspective for network control. Xu et al [1] proposed a flow control method and analyzed the relationship between station capacity and demand based on queuing network theory. Current passenger flow control methods focus on a single station, line, or local network. Existing passenger flow control is mainly based on static relationships between stations and does not consider the timing sequence. This paper optimizes the current flow control method via network controllability according to the characteristics of urban rail transit network and distribution
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