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An Accuracy Position Index Model for Moving Objects on Fixed Network

Temporal and Spatial database of moving objects on fixed network involves frequent updates. Information on query about the historical, present and future positions of moving objects is still limited. The current study propose a new index model (RRH) based on R*- tree, R-tree and Hash table. The R*-Tree is used to index the spatial data of the network. The R Tree forest is employed to index the time intervals. A composite hash table and link list storage structure is used to queries retrieve based on trajectory. The exponential smoothing algorithm is applied to forecast position/speed of the moving objects for a given time. The analysis results show that the proposed model has higher efficiency position prediction.