论文标题
自动检测自行车网络中缺失链接
Automated Detection of Missing Links in Bicycle Networks
论文作者
论文摘要
骑自行车是使城市运输更具可持续性的有效解决方案。但是，自行车网络通常是在缓慢的分段过程中开发的，即使在哥本哈根等良好发达的骑自行车城市中，也会留下大量差距。在这里，我们使用OpenStreetMap的数据开发了用于查找城市自行车网络中最重要的丢失链接的IPDC过程（识别，确定优先，清理，分类）。在此过程中，我们首先确定按照多路复用网络方法的所有可能的差距，根据基于流的指标，新兴的差距群集的优先级，并手动对差距的类型进行分类。我们将IPDC程序应用于哥本哈根，并报告105个最高优先级差距。为了进行评估，我们将这些差距与该市最近的周期路径优先级计划进行了比较，并发现了相当大的重叠。我们的结果表明，具有最小数据要求的网络分析如何用作自行车网络计划的经济高效的支持工具。通过考虑整个城市网络用于整合城市自行车基础设施的网络，我们的数据驱动框架可以补充本地化的手动计划流程，以实现更有效的，更有效的全市决策。
Cycling is an effective solution for making urban transport more sustainable. However, bicycle networks are typically developed in a slow, piecewise process that leaves open a large number of gaps, even in well developed cycling cities like Copenhagen. Here, we develop the IPDC procedure (Identify, Prioritize, Decluster, Classify) for finding the most important missing links in urban bicycle networks, using data from OpenStreetMap. In this procedure we first identify all possible gaps following a multiplex network approach, prioritize them according to a flow-based metric, decluster emerging gap clusters, and manually classify the types of gaps. We apply the IPDC procedure to Copenhagen and report the 105 top priority gaps. For evaluation, we compare these gaps with the city's most recent Cycle Path Prioritization Plan and find considerable overlaps. Our results show how network analysis with minimal data requirements can serve as a cost-efficient support tool for bicycle network planning. By taking into account the whole city network for consolidating urban bicycle infrastructure, our data-driven framework can complement localized, manual planning processes for more effective, city-wide decision-making.
