In this paper, a novel method is proposed for designing a bike network in urban areas. Based on the number of taxi trips within an urban area, a weighted network is abstracted. In this network, nodes are the origins and destinations of taxi trips and the number of trips among them is abstracted as link weights. Data is extracted from the Taxi smart card system of a real city. Then, Communities i.e. clusters of this network are detected using a modularity maximization method. Each community contains the nodes with highest number of trips within the cluster and lowest number of trips with other clusters. Within each community, the nodes close enough to each other for being traveled by bicycle are detected as key points and some non-dominated bike network connecting these nodes are enumerated using a bi-objective optimization model. The total travel cost (distance or time) on the network and the path length are considered as objectives. The method is applied to Isfahan city in Iran and a total of seven regions with some non-dominated bike networks are proposed.

中文翻译：

---

使用网络集群的概念设计自行车网络。

本文提出了一种新的城市自行车网络设计方法。根据市区内出租车的乘车次数，对加权网络进行抽象。在该网络中，节点是出租车行程的起点和目的地，并且行程之间的行程数被抽象为链接权重。数据是从真实城市的出租车智能卡系统中提取的。然后，使用模块化最大化方法来检测社区，即该网络的群集。每个社区都包含节点，该节点在群集内的行程数最高，而与其他群集的行程数最低。在每个社区内，将彼此足够靠近以供自行车旅行的节点检测为关键点，并使用双目标优化模型枚举连接这些节点的一些非支配自行车网络。网络上的总旅行成本（距离或时间）和路径长度被视为目标。将该方法应用于伊朗伊斯法罕市，并提出了总共七个具有非主导自行车网络的地区。