Fusion Research, Based On The Information Of The Taxi Gps Data

With the development of society and economy, the traffic demand is increasing rapidly. The sharp increase of vehicles has been making traffic congestion, accidents and pollution more and more serious, which has become the bottleneck for sustainable development of society. Although the traditional technologies and methods have ameliorated traffic problems to some extent, more limitations and challenges will be encountered in the future. So how to extract traffic data from Vehicle Navigation System (VNS) for information fusion, traffic surveillance and management is the burgeoning cutting-edge technology, which will play an important role in transport system improvement and decision-making.The taxies with navigation systems have the characteristics of high trip-generation rates, long operation time, wide travel area and high occupancy; these are quite suitable for dynamic floating car data collection to research traffic condition and management.In this thesis, based on the literature review and summarization in the areas of GPS navigation system, the methods of data collection, data pre-processing and information fusion are discussed. Firstly, the GPS data format is defined before importing into the database for classification, depositing and pre-processing. Then the data analysis and mining tools are used to analyze and generate the traffic information diagrams and tables for scientific decision-making support. Finally, the traffic information fusion methods are given, and the comprehensive GIS-T platform are established. With the platform, the parameters of taxies operation such as operation status, waiting time, average speed and spatial distribution features can be deduced. This platform can be used to support the taxi station selection and planning, and can be referenced for other traffic management strategies.