A Study on the Coordination of Urban Traffic Control and Traffic Assignment

The interactions between signal setting and traffic assignment can directly affect the urban road network efficiency. In order to improve the coordination of signal setting with traffic assignment, this paper created a traffic control algorithm considering traffic assignment; meanwhile, the link impedance function and the route choice function were introduced into this paper to study the user's route choice and the road network flow distribution. Then based on the above research, we created a system utility value model. Finally through the VISSIM software to simulate the test network, we verified the superiority of the coordination algorithm and the model and gave the optimal flow of the road network. 1. Introduction In urban transportation systems, the equilibrium of the road network supply and demand is an important problem, which can directly impact the road network efficiency. For a fixed road structure and traffic flow, signal setting is the primary influencing factor to traffic supply, and traffic assignment is the primary influencing factor to traffic demand [1, 2]. In order to balance the traffic demand and supply of urban road network and maximize the efficiency of transportation resources, experts and scholars from allover the world have done a lot of research and made great progress in the coordination of signal setting with traffic assignment aspects. Firstly, Allsop [3] and Gartner [4] researched the relationship between signal setting and traffic assignment, and held that signal setting strategy can directly affect user’s route choice and traffic flow distribution. Then they proposed a solution program to traffic equilibrium problem by alternately updating green split signal settings for fixed flows. On these bases, in order to achieve the global optimization, Tan et al. [5] and Smith [6, 7] converted the signal setting and traffic assignment into a hybrid optimization problem. Their research showed that in some actual situation traffic setting even had deteriorated travel time by 30%; thus, they proposed a new signal setting policy under the constraint of stable traffic supply and traffic demand. Subsequently, Gartner et al. [8] and Fisk [9] proposed that we may take the signal setting and traffic assignment as a game problem of Stackberg, which regards traffic managers as superior decision-makers and travelers as subordinate decision-makers. Then, Yang and Yagar [10] proposed a bilevel programming model based on the above method; the model indicated that we can get queuing delay of saturated sections by the network equilibrium parameters