Road-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of memory and disks, and (b) reduces the I/O and communication overhead. There are several road network compression techniques proposed in the literature. These techniques are evaluated by their compression ratios. However, none of these techniques takes into consideration the possibility that the generated compressed data can be used directly in Map-matching operation which is an essential component for all location-aware services. Map-matching matches a measured latitude and longitude of an object to an edge in the road network graph. In this paper, we propose a novel simplification technique, named COMA, that (1) significantly reduces the size of a given road network graph, (2) achieves high map-matching quality on the simplified graph, and (3) enables the generated compressed road network graph to be used directly in map-matching and location-based applications without a need to decompress it beforehand. COMA smartly deletes those nodes and edges that will not affect the graph connectivity nor causing much of ambiguity in the map-matching of objects’ location. COMA employs a controllable parameter; termed a conflict factor \(\mathcal {C}\), whereby location aware services can trade the compression gain with map-matching accuracy at varying granularity. We show that the time complexity of our COMA algorithm is O(|N|log|N|). Intensive experimental evaluation based on a real implementation and data demonstrates that COMA can achieve about a 75% compression-ratio while preserving high map-matching quality. Road Network, Simplification, Compression, Spatial, Location, Performance, Accuracy, Efficiency, Scalability.

道路网络数据压缩或简化可以减小网络的大小，从而占用更少的存储空间，以适应小型路由设备，移动设备或嵌入式系统的需求。简化（a）减少了内存和磁盘的存储成本，并且（b）减少了I / O和通信开销。文献中提出了几种路网压缩技术。这些技术通过其压缩率进行评估。但是，这些技术都没有考虑到生成的压缩数据可以直接用于地图匹配操作的可能性，而地图匹配操作是所有位置感知服务的重要组成部分。地图匹配将对象的测量的纬度和经度与道路网络图中的边线匹配。在本文中，我们提出了一种新颖的简化技术，名为COMA，（1）显着减小了给定道路网图的大小；（2）在简化图上实现了高地图匹配质量；（3）使生成的压缩道路网图可直接用于地图匹配中和基于位置的应用程序，而无需事先对其进行解压缩。COMA巧妙地删除了那些不会影响图形连接性，也不会在对象位置的地图匹配中引起很多歧义的节点和边。COMA使用可控制的参数；称为冲突因子\（\ mathcal {C} \），据此，位置感知服务可以以变化的粒度以地图匹配精度来交换压缩增益。我们证明了COMA算法的时间复杂度为O（| N | l o g | N |）。基于实际实现和数据的密集实验评估表明，COMA可以实现约75％的压缩率，同时保留了较高的地图匹配质量。道路网，简化，压缩，空间，位置，性能，准确性，效率，可扩展性。