Study On Fuzzy Logic System And Its Appilications In Intelligent Transportation System

This dissertation first introduces the development and basic knowledge of fuzzy theory, after that puts the focus on the dynamic fuzzy identification, which is the basis of one of the fuzzy controller design methods. This dissertation also studies the Intelligent Transportation System (ITS), and applies the fuzzy theory in it. The research includes: model identification, control strategy, system evaluation, etc. Reviewing the ITS simulation system, the author proposes an ITS simulating platform integrating the researches in this dissertation. The main works in this dissertation are as following: 1. The dynamic fuzz~?identification is studied, especially the two identification methods. One is modeling the dynamic fuzzy system after investigating a lot of input and output data; the other is T-S model fuzzy identification. On the base of system identification, we can design the fuzzy controller. All above is applied in the linear, non-linear and multi-input multi-output systems through simulation. 2. Classifying them into the differential equation model and the artificial intelligent model, the author reaches car-following models and analyzes the system stability. A nev~ simple-computing fuzzy?car-following model is provided and the simulating result shows its validity. 3. The traffic fuzzy control for single intersection is developed to that for multiple intersections. This control strategy can operate and cooperate the signal lights in a big area and decrease the vehicles?waiting time. 4. Because there are many non-precise and complex variables in the evaluation of ITS, the author proposes a multi-attribute and multi-layer fuzzy evaluation of ITS, considering both qualitative and quantitative items. After integrating the two classes of the grading evaluating conditions, we get the outcome. This method suits very much the evaluation of a complex sYstem comprising both precise and non-precise variables, such as the evaluation of ITS. 5. Having summarizing the present ITS simulation system, the author structures an ITS simulating platform integrating the research fruits of car-following model, control method and fuzzy evaluation in this dissertation. Finally, the dissertation concludes with a summary and perspectives of future research.