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A spatio-temporal data model for road network in data center based on incremental updating in vehicle navigation system

机译：基于车辆导航系统增量更新的数据中心道路网络时空数据模型

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摘要

The technique of incremental updating, which can better guarantee the real-time situation of navigational map, is the developing orientation of navigational road network updating. The data center of vehicle navigation system is in charge of storing incremental data, and the spatio-temporal data model for storing incremental data does affect the efficiency of the response of the data center to the requirements of incremental data from the vehicle terminal. According to the analysis on the shortcomings of several typical spatio-temporal data models used in the data center and based on the base map with overlay model, the reverse map with overlay model (RMOM) was put forward for the data center to make rapid response to incremental data request. RMOM supports the data center to store not only the current complete road network data, but also the overlays of incremental data from the time when each road network changed to the current moment. Moreover, the storage mechanism and index structure of the incremental data were designed, and the implementation algorithm of RMOM was developed. Taking navigational road network in Guangzhou City as an example, the simulation test was conducted to validate the efficiency of RMOM. Results show that the navigation database in the data center can response to the requirements of incremental data by only one query with RMOM, and costs less time. Compared with the base map with overlay model, the data center does not need to temporarily overlay incremental data with RMOM, so time-consuming of response is significantly reduced. RMOM greatly improves the efficiency of response and provides strong support for the real-time situation of navigational road network.
机译：增量更新技术可以更好地保证导航地图的实时性，是导航路网更新的发展方向。车辆导航系统的数据中心负责存储增量数据，而用于存储增量数据的时空数据模型确实会影响数据中心对来自车辆终端的增量数据要求的响应效率。通过分析数据中心使用的几种典型时空数据模型的不足，并基于带叠加模型的底图，提出了带叠加模型的逆向图（RMOM），以使数据中心快速响应。增量数据请求。 RMOM支持数据中心不仅存储当前完整的道路网络数据，而且还存储从每个道路网络更改到当前时刻的增量数据覆盖图。设计了增量数据的存储机制和索引结构，并开发了RMOM的实现算法。以广州市的导航路网为例，通过仿真测试验证了RMOM的有效性。结果表明，数据中心中的导航数据库仅通过一个RMOM查询就可以响应增量数据的需求，并且花费的时间更少。与具有覆盖模型的基础地图相比，数据中心不需要使用RMOM临时覆盖增量数据，因此显着减少了响应时间。 RMOM大大提高了响应效率，并为导航路网的实时情况提供了有力的支持。

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