考虑拥挤度的城市轨道交通乘客时空路径还原方法
蔡金
Method for Restoring Urban Rail Transit Passenger Spatio-Temporal Paths in Consideration of Congestion
CAI Jin
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作者信息:重庆市轨道交通（集团）有限公司， 401120， 重庆
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Affiliation:Chongqing Rail Transit (Group) Co., Ltd., 401120, Chongqing, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2024.06.003
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中图分类号/CLCN:U293.13
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栏目/Col:研究报告
摘要:
［目的］客流是城市轨道交通运营管理的支撑，在城市轨道交通日益发展的情况下，对客流精细化和准确度的要求越来越高。为提高客流分配的精确性，需要研究城市轨道交通时空路径选择的流程方法。［方法］针对城市轨道交通特点，基于换乘站网络简化线网结构模型，改进了各OD（起讫点）之间的短路径计算方法；结合路径费用容许区域的相对阈值和绝对阈值，筛选有效物理路径；根据进出站走行时间、换乘走行时间和列车时刻表等数据构建时空路径，并搜索可行时空路径集合；利用仿真理念，以时间推演来还原站台候车过程中列车拥挤度对乘客上车行为的影响，从微观层面合理判断乘客选择的时空路径，叠加个体时空位置形成线网客流时空分布状态。［结果及结论］南宁地铁实例表明，乘客时空路径还原方法以进出站OD为源数据，不仅可以输出传统的换乘量和断面客运量，还能进一步输出精细的乘客OD时空数据和列车上下车客流数据，从而弥补微观客流数据的空白。
Abstracts:
［Objective］ Passenger flow is the pillar for operation and management of urban rail transit. With the increasing development of urban rail transit, the demand for meticulous and accurate passenger flow analysis is getting higher and higher. To improve the accuracy of passenger flow allocation, it is necessary to study the process and method of passenger spatio-temporal path selection in urban rail transit. ［Method］ Firstly, according to the characteristics of urban rail transit, the shortest path algorithms between various ODs (original and destination) is improved based on the simplified network structure model of the transfer station network. Secondly, based on the relative and absolute thresholds for path cost allowable area, the effective physical path is screened. Then the spacio-temporal paths are constructed according to the data including the passenger entry and exit time, the walking time for transfer and the train schedule, and the set of feasible spacio-temporal paths is searched. Finally, with the simulation concept, the influence of train congestion on passenger boarding behavior is restored through time evolution, and passengers′ choices of spacio-temporal paths are reasonably determined from the microscopic level, and the spacio-temporal distribution state of passenger flow in the network comes into being with the superimposed individual spacio-temporal positions. ［Result & Conclusion］ The example of Nanning Metro shows that with inbound and outbound OD as the source data, the proposed method can output not only the traditional passenger transfer volume and sectional passenger flow volume, but also the elaborate passenger OD spacio-temporal data as well as the passenger flow on and off trains data, making up the gap of micro passenger flow data.
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