现有的匹配路段初筛系统都采用基于磁盘文件的数据库系统作为路网数据及其与网格间索引数据的存储容器。当有大规模GPS数据要进行处理时，传统磁盘数据库由于内外存交换开销过大导致无法支持数据的实时、高吞吐量处理。为此，本文将内存数据库引入匹配路段初筛系统中，通过将现有的初筛算法和内存数据库相结合，实现了一个测试系统。实际数据测试结果表明，本文的方法将匹配路段初筛系统的检索性能提高了3倍，有效提升了匹配路段初筛环节的处理速率和吞吐量。

The existing initial filtering systems of matching road all the database based on the disk file to store road network data and grid index. Due to the big overhead between in and out memory, the traditional disk database fails to support real-time and high throughput processing of the large-scale GPS data. To address this issue, this paper imports main memory database into the system. We built a test system by integrating the existing filtering algorithm and the MM-DB. The experimental result demonstrates that our method improves the search performance of the system up to 300% and promotes the speed and throughput of the system effectively.