【摘要】 城市地铁-公交网络站点交叉重叠、线路复杂，高峰时段的客流潮汐现象下，布局不合理的交通网络难以资源互补，导致线路换乘乘客出行耗时延长、交通碳排放量增大。为此，提出改进蚁群算法下城市地铁-公交耦合网络布局效率优化方法。该方法通过耦合站点对和耦合距离完成城市地铁-公交耦合网络中交叉重叠线路、站点的复杂拓扑结构连接，实现地铁-公交交通资源互补；基于拓扑结构，设计换乘乘客出行耗时和交通碳排放量减少的换乘站点布局目标函数，以及碳排放效益最大化的约束条件，以解决换乘乘客出行耗时延长、交通碳排放量增大问题；改进传统蚁群算法的信息素挥发系数的自适应设置方法，快速求解满足目标函数与约束条件的地铁-公交耦合网络换乘站点位置、线路走向的布局方案。研究结果显示：该方法可以将复杂的城市地铁-公交耦合换乘网络用耦合站点对和耦合线路关联起来，完成耦合建模。本文方法改进蚁群算法后，算法对布局优化方案的求解时长最大值低于1 s，明显小于优化前。城市地铁-公交耦合网络布局优化后，换乘乘客的换乘步行距离变化值为-16 m，步行时间缩短-5.46%。换乘乘客的出行总时间减少1.18 h。城市地铁-公交耦合网络换乘效率提升，碳排放效益显著，且求解布局优化方案时更加高效。更多还原

【Abstract】 The intersection and overlap of urban subway and bus network stations, the complexity of routes, and the tidal phenomenon of passenger flow during peak hours make it difficult for the transportation network with unreasonable layout to complement resources, resulting in longer travel time and increased carbon emissions for passengers transferring between routes. To this end, an improved ant colony algorithm is proposed to optimize the efficiency of urban subway bus coupling network layout. This method completes the complex topology connection of overlapping lines and stations in the urban subway bus coupling network by coupling station pairs and coupling distances, achieving complementary subway bus transportation resources; based on topological structure, design the objective function of transfer station layout to reduce the travel time and transportation carbon emissions of transfer passengers, as well as the constraint conditions to maximize carbon emission benefits, in order to solve the problems of prolonged travel time and increased transportation carbon emissions of transfer passengers; improve the adaptive setting method of pheromone volatilization coefficient for traditional ant colony algorithm, and quickly solve the layout scheme of subway bus coupling network transfer station location and route direction that meets the objective function and constraint conditions. The research results show that this method can associate complex urban subway bus coupling transfer networks with coupling station pairs and coupling lines to complete coupling modeling. After improving the ant colony algorithm, the maximum solution time for layout optimization schemes in this article is less than 1 second, which is significantly lower than before optimization. After optimizing the layout of the urban subway bus coupling network, the change in walking distance for transfer passengers is-16 m, and the walking time is reduced by-5.46%. The total travel time of transfer passengers decreased by 1.18 hours. The coupling network between urban subway and public transportation has improved transfer efficiency, significant carbon emission benefits, and is more efficient in solving layout optimization solutions.更多还原