基于粒子群算法的城市快速轨道交通线网规划方法

Urban Rapid Rail Transit Network Planning Based on Particle Swarm Optimization

既有交通线网规划方法主要针对居民出行需求展开规划,与早晚高峰期间人流聚集、交通压力大等适应性较差,通行时间较长,影响了交通线网的规划效果。设计了基于粒子群算法的城市快速轨道交通线网规划方法:提取城市快速轨道交通特征,找出交通压力的主要来源;针对交通压力来源等情况,预测城市轨道交通线网需求;利用粒子群算法构建出交通线网规划模型,搜索全局最优道路反馈给线网规划,进而提升城市轨道交通线网规划的实效。采用对比实验的方式,验证了该方法的规划效果更佳、出行时间更短,可应用于实际规划工作。

In the conventional traffic network planning methods,it is mainly aimed at the residents'travel demand planning,but it is easy to suffer from greater traffic pressure during the morning and evening peak periods,which increases the traffic time and affects the planning effect of the traffic network.Therefore,an urban rapid rail transit network planning method based on particle swarm optimization algorithm is designed.Extract the characteristics of urban rapid rail transit,find out the main sources of traffic pressure,predict the demand of urban rail transit network according to the existing traffic situation,and then use particle swarm optimization algorithm to build a traffic network planning model,search for the global optimal road,thus improving the effectiveness of urban rail transit network planning.By means of comparative experiments,it is verified that the planning effect of this method is better and the travel time is shorter,which can be applied to real life.