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基于乘客路径选择的多制式轨道交通客流分配
引用本文:倪少权,杨皓男,彭强.基于乘客路径选择的多制式轨道交通客流分配[J].交通运输系统工程与信息,2021,21(1):108-115.
作者姓名:倪少权  杨皓男  彭强
作者单位:1. 西南交通大学,交通运输与物流学院,成都 610031;2. 综合交通运输智能化国家地方联合工程实验室,成都 610031; 3. 综合交通大数据应用技术国家工程实验室,成都 610031;4.中国铁路成都局集团有限公司,成都 610031
基金项目:国家重点研发计划/ National Key Research and Development Program of China(2017YFB1200702);国家自然科学基金/National Natural Science Foundation of China(52072314);四川省科技计划项目/Sichuan Science and Technology Program (2020YFH0035)。
摘    要:为量化换乘对乘客出行路径选择的影响程度,在单层网络中添加虚拟换乘站,构建无隐性连接的三层多制式轨道交通拓扑网络模型。基于时间、换乘节点衔接性,计算线网间衔接性系数;利用Dijkstra法搜索模型各起讫点间的 K 短路径,以乘客感受到的线网复杂度及乘客出行计划确定时间,建立乘客对线网的熟悉度函数;根据乘客路径选择影响因素构建广义出行费用,利 用Logit函数对每条路径的选择概率进行计算;最后设计客流分配算法进行求解,实现对多制式轨道交通网络的客流分配。以成都地铁、成灌、成贵高铁等线路建立多制式轨道交通网络仿真模型,对其客流分配实例分析表明,客流的分配结果与实际数据基本吻合,证实了客流分配算法的真实有效性。

关 键 词:铁路运输  客流分配  出行路径选择  多制式轨道交通  线网熟悉度  Logit模型  
收稿时间:2020-09-28

Passenger Flow Distribution of Regional Multi-standard Rail Transit Based on Passenger Route Selection
NI Shao-quan,YANG Hao-nan,PENG Qiang.Passenger Flow Distribution of Regional Multi-standard Rail Transit Based on Passenger Route Selection[J].Transportation Systems Engineering and Information,2021,21(1):108-115.
Authors:NI Shao-quan  YANG Hao-nan  PENG Qiang
Institution:1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China; 2. National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation, Chengdu 610031, China; 3. National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Chengdu 610031, China;4.China Railway Chengdu Bureau Group Co. Ltd, Chengdu 610031, China
Abstract:To quantify the impact of passengers' transfer on their travel route selections, this study added virtual transfer stations to the single-layer network, and developed a three-layer multi-standard rail transit topology network model without hidden connections. The connectivity coefficient between networks was calculated based on the time and transfer node connectivity. A function was established to describe the passenger's familiarity to the line network. In this function, the Dijkstra method was used to search for the K short path between the start and end points of the model, and the time was determined in consideration of passengers' travel plans and the complexity of the line network from the passengers' perspectives. A generalized travel cost function was also established to reflect the factors affecting the passenger path selection. The Logit model was used to calculate the selection probability for each route. The passenger flow distribution algorithm was designed to solve the model and then complete the passenger flow distribution to the multi-standard rail transit network. The multi-standard rail transit network simulation model was based on the Chengdu Metro, Chengguan, Chenggui High-speed Railway lines, etc. The passenger flow distribution examples analysis show that the passenger flow distribution results are basically consistent with the actual data, which confirms the authenticity and effectiveness of the passenger flow distribution algorithm.
Keywords:railway transportation  passenger flow distribution  travel route selection  multi- standard rail transit  line network familiarity  Logit model  
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