Route Selection Model And Algorithm Based On Uncertain Preference And Fuzzy Decision

With the development of economy, the contradiction between the growth of traffic volume and the road condition is becoming prominent, which has greatly restricted the development of social economy. The research on multi-lane traffic flow model, routing choice model and its algorithms can not only benefit the balanced distribution for traffic and travelers in route networks, but also reduce traffic load. The research will provide new ideas to improve the traffic congestion situation and to provide theory and methods to the building of Intelligent Transportation System. This thesis consists mainly of two parts:(1) A summary of traffic flow theory is presented about some important models and their development in different period, especially the cellular automata (CA) models. In chapter 2, based on the CA models, an improved traffic flow model with mixed vehicles in accordance with real traffic in China is proposed. The study focuses on three-lane highway. The influence of driver's characters on their driving behaviors is discussed and a framework for modeling human-like driving behaviors is provided using fuzzy logic method. On the framework the vehicle's lane-changing behavior is mainly studied and some basic fuzzy rules for drivers of three types are constructed. With the simulation data, the characteristics of mixed vehicles are analyzed.(2) Travelers will choose the best way if there exist many routes to destination. In chapter 3, the route choice model and algorithms is proposed based on vague set. Multi-criteria fuzzy decision-making methods based on vague set theory are creatively applied into urban traffic system. According to the analysis of the multi-objective attribute of the route choice optimization, a multi-objective programming model is proposed for the optimization of route choice. The solution of the model is a comprehensive satisfied route, which can reflect the diversity features of information demand and objective demand for urban traveler. Some examples are given to show the rationality and effectiveness of the model. Using the theory, travelers can actively select the satisfied routes, and the whole traffic situation in the road network can be improved as a result.