Abstract: In order to solve the problems in the transfer process connection and collaboration of metro-bus two-layered network faced by the passengers making route selection in the urban transportation network, such as the far distance between some transfer stations, the unclear connection orientation and the imbalance between supply and demand in local transfer, a collaborative optimization method for urban traffic networks based on two-layered complex networks was presented. Firstly, the logical network topology method was applied to the topology of the urban transportation network, and the metro-bus two-layered network model was established by the complex network theory. Secondly, with the transfer station as research object, a node importance evaluation method based on K-shell decomposition method and central weight distribution was presented. This method was able to realize coarse and fine-grained divison and identification of metro and bus stations in large-scale networks. And a collaborative optimization method for two-layered urban traffic network with mutual encouragement was presented, that is to say the method in the complex network theory to identify and filter the node importance in network topology was introduced to the two-layered network structure optimization. The two-layered network structure was updated by identifying high-aggregation effects and locating favorable nodes in the route selection to optimize the layout and connection of stations in the existing network. Finally, the method was applied to the Chengdu metro-bus network, the existing network structure was optimized to obtain the optimal optimized node location and number of existing network, and the effectiveness of the method was verified by the relevant index system. The results show that the global efficiency of the network is optimized after 32 optimizations, and the optimization effect of the average shortest path is 15.89% and 16.97%, respectively, and the passenger transfer behavior is increased by 57.44 percentage points, the impact on the accessibility is the most obvious when the travel cost is 8000-12000 m with the optimization effect of 23.44% on average. At the same time, with the two-layered network speed ratio and unit transportation cost introduced, the response and sensitivity difference of the traffic network to the collaborative optimization process under different operational conditions are highlighted.

Key words: urban transportation network, two-layered complex network, cooperative optimization, node evaluation, cooperative strength

摘要： 针对城市交通网络中旅客在公共交通出行路径选择时面临的地铁与公交双层网络在换乘衔接协同中存在的部分换乘站点之间距离过远、衔接导向不明确、局部换乘供需不平衡等问题，提出基于双层复杂网络的城市交通网络协同优化方法。首先，采用逻辑网络拓扑方法对城市交通网络进行拓扑，并基于复杂网络理论建立地铁-公交双层网络模型。然后，以换乘车站为研究对象，提出一种基于K-shell分解法和中心性权重分配的节点重要度评价方法，对大规模网络中的地铁、公交车站进行粗粒度和细粒度划分和识别，并在此基础上提出一种相互激励的双层城市交通网络协同优化方法，即在双层网络结构优化中引入复杂网络理论中对于网络拓扑中节点重要度的识别和筛选方法，通过对路径选择中高集聚效应的识别和有利节点的定位更新双层网络结构以优化现有网络的车站布局和衔接关系。最后，将提出的方法应用于成都市地铁-公交网络，优化了现有网络结构，得到了现有网络的最佳优化节点位置和优化数量，并且通过相关指标系统验证了该方法的有效性。实验结果表明，采用该方法优化32次后的网络全局效率达到最优，和平均最短路径的优化效果分别为15.89%、16.97%，旅客换乘行为提升57.44个百分点；优化方法对旅行成本在8000~12000 m的可达性影响最明显，优化效果平均达到23.44%；同时引入双层网络速度比和单位交通成本比，突出了不同运营状况下交通网络对协同优化过程的反应和敏感度的不同。

关键词: 城市交通网络, 双层复杂网络, 协同优化, 节点评价, 协作强度