Distributed Data Mining And Navigating Of Dynamic Traffic Information

Intelligent Transportation System (ITS) is a transportation service system which is based on the modern electronic information technology; it has became a kind of development trend. The research of ITS focuses on the traffic information collection, processing and dissemination. With more domestic vehicles equipped with GPS devices and the development of the wireless communication technology, it offers a good support for traffic information collection and dissemination. This thesis designs and realizes a distributed data mining and navigating system based on the dynamic traffic information collected by floating cars.As for the design of distributed system architecture, it divides the city electric map into many sub-blocks to ensure every node just stores part of the data, and then reduces the local computational pressure. In order to achieve the intelligent navigation in different regions, it layers the map according to the map attributes and uses hierarchy guidance algorithm. When the navigation has to be finished between different regions, it can choose the road of higher level. At the same time, to maintain data consistency in the whole system, it also designs a network module to migrate the historic traffic data and the dynamic update of the road conditions, and then makes the traffic condition consistent in every regions.In general, this system uses the dynamic traffic data to calculate the real-time road condition, updates the relevant road network, responds the navigation request and then shows the navigation paths and the current road condition on the third-party map software.In order to verify the effectiveness and applicability of this distributed system, it uses the real GPS data and the latest Beijing electronic map to carry out function test and performance test, the running result is satisfied.