Research On Intelligent Algorithms Of Vehicle Navigation Based On Fuzzy Theory

This dissertation mainly focuses on the theories and intelligent algorithms of vehicle navigation based on Fuzzy theory. The main works and contributions are summarized as follows:1. The vehicle navigation related technologies and fuzzy theory technology basics are introduced in details. The vehicle navigation filtering technology and fuzzy theory technology are reviewed, as well as fuzzy technology in traffic information processing technology is applied. The advantage of Fuzzy theory is analyzed, and its application in the vehicle navigation system is reasonable and feasible.2. The intelligent adaptive filtering algorithm based on fuzzy control is studied in details. It is based on adaptive filtering algorithm. An intelligent adaptive filtering algorithm based on fuzzy control is set up. First a discriminating statistic is constructed by filtered data residuals. Second a fuzzy controller is constructed by this discriminant statistic amount. At last adaptive factor of adaptive filtering is controlled by this fuzzy controller. The new algorithm can not only counterpoised information of dynamical model and observations, but control the influences of the model errors on the navigation results.3. The intelligent fading filtering algorithm based on fuzzy control is studied. The algorithm is based on residual deviation, and fading factor of fading filtering is constructed by fuzzy theory. The new algorithm is accurate than the old.4. The intelligent optimal path algorithm based on fuzzy theory is studied. The model of path choice degree based on static traffic information, dynamic traffic information, human subjective decisions and so on, is set up. Membership function is constructed at the same time. It is shown that the algorithm can provide the optimal path for travelers.5. The travel time prediction algorithm based on the fuzzy control is studied. Time series data is regulated by smoothing coefficient, then forecast results are affected. Fuzzy controller is constructed to control smoothing coefficient. Travel time prediction of the next period is corrected, travel time prediction accuracy and intelligent level are improved.6. Intelligent travel time prediction algorithm based on fuzzy comprehensive judgment is studied. A huge advantage is had by the technology in dealing with the issue of non- linear relationship. Influence of various factors predicted travel time will be affected. Intelligent travel time is achieved by assigning various factors.7. The subscription/notification mode dynamic traffic information service mode is studied. A new service mode is put forward. The service mode is applied in the dynamic traffic information system.8. Fuzzy XML data model is established, and dynamic traffic information intelligent network services middleware is constructed. It is described by the different data source dynamic traffic information data, and is achieved by heterogeneous data integration data interoperability. Dynamic traffic information in Application Environment and heterogeneous data structures are shielded. Dynamic traffic information service is provided.9. The distributed dynamic traffic information intelligent network service is studied. Because it has distributed, active service, on-demand services and intelligence services, etc. Timeliness and traffic condition are reflected ful y by its advantage.