Title: Graph Simplification Solutions to the Street Intersection Miscount Problem Show Chinese title

Title: 图简化解决方案解决街道交叉口误计问题

Abstract: Street intersection counts and densities are ubiquitous measures in transport geography and planning. However, typical street network data and typical street network analysis tools can substantially overcount them. This paper explains why this happens and introduces solutions to this problem. It presents the OSMnx package's algorithms to automatically simplify graph models of urban street networks -- via edge simplification and node consolidation -- resulting in faster, parsimonious models and more accurate network measures like intersection counts/densities, street segment lengths, and node degrees. Then it validates these algorithms and conducts a worldwide empirical assessment of count bias to quantify the motivating problem's prevalence. A full accounting of this bias and better methods to attenuate misrepresentations of intersections are necessary for data-driven, evidence-informed transport planning. Show Chinese abstract

Abstract: 道路交叉口数量和密度是交通地理学和规划中的常见度量。 然而，典型的城市道路网络数据和典型的道路网络分析工具可能会显著高估这些数值。 本文解释了为什么会发生这种情况，并介绍了对此问题的解决方案。 它介绍了OSMnx包的算法，通过边简化和节点合并自动简化城市道路网络的图模型，从而得到更快、更简洁的模型，以及更准确的网络度量，如交叉口数量/密度、道路段长度和节点度数。 然后，它验证了这些算法，并进行了全球范围的经验评估，以量化该问题的普遍性。 对这种偏差进行全面的核算以及更好的方法来减少交叉口的误表示，对于数据驱动和基于证据的交通规划是必要的。