Research On Models Of Congestion Forecast And Control Based On Systems Science Theories

In recently years, with acceleration of socio-economic development in China, the number of vehicles in urban areas increases rapidly, the traffic congestion has become more and more seriously year after year, so that traffic congestion in big cities has been a big problem concerned by many governments in the world today. Although governments in some big cities expend a huge sum of money to develop the Traffic Flow Guidance Systems (TFGS), the Intelligent Transportation Systems (ITS) or the models of the best way to solve the problem of local congestion in urban networks, the congestion problem has not been solved radically, and there are still numerous obstacles in using these systems and models.How to maintain the unblocked transportation in urban networks? How to solve the traffic congestion problem? Focusing upon two of those problems, namely congestion and fluctuation, this dissertation researches into models of congestion forecast and control based on systems science theories—Dissipative Structure Theory, Synergetic Theory, Catastrophe Theory, Core and Coritivity Theory and so on. The central contents in this dissertation are as follow:1)Looking back the process of people to recognize system, and presenting the framework of systems science theories.The modern systems science theories involve Fuzzy System Theory, Dissipative Structure Theory, Synergetic Theory, Catastrophe Theory, Magni-System Theory, Super- Circular Theory, Chaos Theory, Renormalization Group Theory and so on. This dissertation sets forth the principle of system teleology, analyzes the dynamic evolvement process of systems, summarizes the development phases of the modern systems and the types of systems science methods, and addresses that the research methods of systems science adapt to the research of urban traffic system.2)By analyzing the characteristic of urban traffic system and describing the inner and the outer of the urban traffic system, this dissertation sets forth that the urban traffic system is an open system, and is also a kinetics system. By summarizing the predecessor's work, this dissertation analyzes the countermeasures of reducing traffic congestion and generalizes the key approaches of the predecessor.3)By defining the order parameters of traffic arc for the order or disorder, this dissertation proposes the best scheme becoming from disorder to order by establishing the mathematic programming models and resolving them.4)This dissertation deals with the fluctuation and spring of traffic flow on road links, and presents a dynamic mathematical model formulating the traffic flow self-organization after fluctuation. In terms of the principle that the utmost traffic flow can result in the greatest traffic saturation, the model is simplifies and applied to forecast the traffic congestion associated with fluctuation by means of Monte Carlo method.5)Based on the dynamic user state equilibrium conditions, this dissertation proposes a dynamic state traffic assignment model which is a compromise between dynamic trafficassignment model and static traffic assignment model. The dynamic traffic assignment model and dynamic state traffic assignment model are applied to solve the traffic congestion problem.6)This dissertation expounds that urban road-traffic system is a dissipative structure system, and it possesses both local traffic state limit and local self-control of system. By referred to the theory of thermodynamics for characteristics of dissipative structure system, the congregation and diffusion of traffic flow are studied, and the traffic congestion control methods associated with their finished time are proposed.7)In this dissertation, the basic ideas and slaving principles of synergetics are introduced,including the conception of the self-organizations of different layered description of traffic system and the self-organized courses of fluctuation and spring. Based on the analysis of linear stability of parameter equations of traffic system and the derivation and the solution of the order parameter equation, the traffic congestion control method is given.8)In this dissertation, we introduce three special shapes of urban traffic congestion and five essential characters of catastrophe, and expound that the traffic catastrophes are contained in urban traffic congestion. We apply catastrophe theory to traffic congestion control modelling, and give three examples of application to test the effectiveness of this method. Finally, we present some advices to reduce urban traffic congestion.9)In this dissertation, we propose a BP self-organizing neural network, a Hopfield self-organizing neural network, a wavelet fuzzy self-organizing neural network and a structure self-organizing neural network, and apply all of them in the control of the congregation of traffic flow.10)Based on the core and coritivity of the non-directional connected network system, a method of calculating the core and coritivity of the directional connected network system is proposed in this dissertation, and is applied in calculating the dynamic core and coritivity of the dynamic flow network system. In this dissertation, we set forth that the traffic network system is the dynamic flow network system, and present the algorithm of calculating the dynamic core and coritivity of the traffic network system.11) Based on the catastrophe theory, the spripro principle and the hypercycle theory, the evolvement process of urban traffic is studied. The congestion control method of traffic is given based on the evolvement process of urban traffic.