基于社团结构发现的公交专用道施划影响分析

城市道路施划公交专用道是保障公交优先的重要举措，但会压缩社会车辆的运行空间，使得高峰期部分社会车辆不得不选择其他道路出行，从而对路网中其他交通流运行造成影响，严重时可能会引发更大范围的拥堵.因此，准确确定施划公交专用道后的交通影响范围是城市交通管理、控制与诱导策略制定的依据.本文结合城市路网的复杂网络结构特性及网络动力学基础，认为影响范围内的路段间存在相似性，可将问题转化为复杂网络的社团结构发现进行研究.以对偶拓扑的方式获取城市路网结构，通过改进的随机行走转移概率推导出网络节点相异度，采用凝聚算法划分出路网社团结构以确定影响范围.最后对北京市京通快速路施划公交专用道的实例进行数值分析和对比研究，证明了本文研究方法的可行性，也可为交通领域相关研究提供新的研究思路及方法.

Transport Influence Analysis of Bus Lanes Based on Community Structure Detection

Designation of bus lanes is an important measure to protect public transport priority. However, it will compress running space of vehicles. So part of the vehicles have to choose other sections in the peak hours, that can affect other vehicles on the other road. In order to research the influencing regions, we transfer it into process of the data sample cluster, this paper proposes here a measure for community structure detection of similarities between vertices based on random walks, which combines topologies of complex network and epidemic dynamic. This algorithm improves the transition probability of random walk that particles transfer between nodes in the network, not only relate to the degree of nodes, but to the distance between nodes. It deduces dissimilarity by transition probabilities and based on it. It uses hierarchical clustering to build a tree for final community structure. A case study on Jingtong Expressway in Beijing shows the urban traffic network proved the feasibility of this method, which can also provide new research ideas and methods to relevant research works.