摘要
为了实现大规模人群聚集的风险防控,文章基于北京市地铁城市轨道交通自动售检票系统数据即AFC数据,在识别乘客路径的基础上,考虑城市轨道交通运输能力、客流需求等因素,建立使乘客滞留时间最小化、广义乘客出行时间最小化的多目标规划模型,实现了同时考虑地铁系统与乘客需求的最优规划。最后以北京市通勤线路"八通线"为例分析了车站限流前后总出行时间与平均出行时间两个指标的变化以及限流车站数目的灵敏度,为城市轨道交通高峰运营策略下的运营安全提供了借鉴意义。
In order to prevent and control the risk of large-scale crowd gathering,based on the data of Beijing Subway Urban Rail Transit Automatic Fare Collection data,also known as AFC data,for the purpose of identifying passenger paths,this paper establishes a multi-objective programming model to minimize passenger detention time and general passenger travel time by identifying passenger paths and considering urban rail transit transport capacity,passenger flow demand and other factors.Meanwhile,the optimal planning considering both subway system and passenger demand is realized.Finally,based on the"Batong Line"of Beijing commuter line,this paper analyzes the comparison between the decision of the current limiting station and the comparison before and after the flow limiting,which provides a reference for the operation safety under the peak operation strategy of urban rail transit.
出处
《科技创新与应用》
2021年第20期80-82,共3页
Technology Innovation and Application
关键词
AFC数据
城市轨道交通
高峰限流
多目标优化
AFC Data
urban rail transit
peak flow limiting
multi-objective optimization
