ABSTRACT As one of the major concerns in cartographic generalization, road network generalization aims at maintaining the patterns of road networks across map scales. Previous methods define the pattern of road networks mainly from the perspectives of geometry and topology. However, for navigation purposes, traffic flow information is also important to generalize road networks. More specifically, road segments that have a proximity relationship in the traffic flow system should be retained together on small-scale maps to preserve the completeness of the driving route. In this regard, this study proposes an improved method for road network generalization that considers network geometry, topology, and traffic flow patterns. First, strokes are constructed from the road network data based on the ‘every best fit’ geometric principle. Then, the relationships among strokes are developed on the basis of traffic flow patterns, which are extracted from taxi trajectory data. The strokes are then selected in sequence based on the indicators of geometry, topology, and traffic flow. Our experimental results demonstrate that the proposed method can preserve both the ‘Good Continuity’ principle and the transport function relationship of roads after generalization.

中文翻译：

---

考虑交通流模式的路网泛化

摘要 作为制图泛化的主要关注点之一，道路网络泛化旨在维护跨地图比例的道路网络模式。以往的方法主要从几何学和拓扑学的角度来定义道路网络的格局。然而，出于导航目的，交通流量信息对于概括道路网络也很重要。更具体地说，在交通流系统中具有邻近关系的路段应该一起保留在小比例地图上，以保持行驶路线的完整性。在这方面，本研究提出了一种改进的道路网络泛化方法，该方法考虑了网络几何、拓扑和交通流模式。首先，笔画是根据“每一个最佳拟合”几何原理从道路网络数据构建的。然后，笔画之间的关系是根据从出租车轨迹数据中提取的交通流模式开发的。然后根据几何、拓扑和交通流的指标依次选择笔画。我们的实验结果表明，所提出的方法可以保留“良好连续性”原则和泛化后道路的运输功能关系。