Research On Traffic Demand Control Using The Two-fluid Theory For The Sensitive Areas Of Urban Networks

Accurately determining the macroscopic traffic conditions of sensitive areas in urban networks, which lays foundation for the traffic demand control and vehicle route guidance systems, which is also an important component of Advanced Traveler Information System. It is the prerequisites that considering the influence of the topological feature, traffic trip distribution and signal control for the network conditions. The domestic and international scholars have made some research in the field of estimating traffic conditions, however, the study purpose mainly focused on the justifying traffic states, they did not taking account the need of traffic control during choosing the traffic state parameters, therefore the state parameters build the relationship between the macroscopic traffic conditions and traffic control. This paper proposes the macroscopic traffic variables which are suitable for the signal control, and then the relations between the traffic variable are derived by applying the two-fluid theory, the macroscopic traffic conditions model of sensitive area in urban networks; learning from the thinking about equation of state of complex systems, the ordinary differential equations for the sensitive area system is derived. By combining the macroscopic traffic conditions model with the ordinary differential equations or the sensitive area system, this paper build the relationship between the macroscopic traffic conditions and traffic demand control. This paper mainly study three components.(1) through analyzing and summarizing the state variables in the traffic condition models, this paper propose the criteria for choosing the macroscopic traffic variables, which is suiting to the traffic control, and then the macroscopic traffic variables are determined. The relations between the traffic variables are derived by applying the two-fluid theory. Therefore, the macroscopic traffic condition model of urban networks is developed; and the calculation method of the optimal network capacity is presented based on this model. The model parameters are calibrated by using the least square method. At the same time, the model is applied for different network and signal control. This proposed model can identify the influence of the topological feature and signal control.(2) Through comparative analysis the urban network and complex systems, this paper takes the sensitive areas as a complex, nonlinear system, respectively analysis the process of traffic jam for a simple lane system and network system. And drawing lessons from thinking about equation of state of complex systems and determining system variables such as inflow variables, outflow variable and internal state variable, the paper derives the ordinary differential equations for the sensitive areas.(3) To combine the macroscopic traffic condition model with the he ordinary differential equations for the sensitive areas, the paper develops the relationship between traffic states and signal control. At the same time, applying VISSIM traffic simulation software comparatively analysis macroscopic traffic conditions between taking signal control and not taking signal in sensitive areas of urban networks.