轨道交通新线客流后评估分析
李珂杨慧芳乐北晨
Post-evaluation and Analysis of Passenger Flow on New Rail Transit Lines
LI KeYANG HuifangYUE Beichen
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作者信息:武汉地铁运营有限公司， 430030， 武汉
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Affiliation:Wuhan Metro Operation Co., Ltd.，430030， Wuhan， China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2025.05.007
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中图分类号/CLCN:U293.13
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栏目/Col:规划与投融资
摘要:
［目的］在城市轨道交通建设和运营中，提高新线客流预测精度已逐渐成为轨道交通行业关注的重点问题之一，因此有必要对传统新线客流预测方法进行评估、改进和优化。［方法］介绍了武汉地铁的新线开通情况，分析了武汉地铁新开线路的客运量走势规律，以及预测客流与实际客流的对比情况；基于线路客运量、分站客流量、断面客流量等客流指标，分析了预测客流产生误差的原因；提出了新线客流预测方法的改进建议。［结果及结论］预测方法自身的局限性、线路及车站属性考虑不足，以及预测基础数据不足等因素，是导致新线客流预测产生误差的主要原因，新冠疫情影响客流培育、基于服务角度考虑等因素是导致新线客流预测产生误差的次要原因。提高新线客流预测精度的方法主要包括：优化相关预测参数；通过引入修正系数浮动因子加强对不同线路及车站的属性分析；加强城市交通基础数据的积累，以及客流敏感性分析；探索新线客流预测新方法，或对传统预测方法进行动态优化。
Abstracts:
［Objective］
In the construction and operation of urban rail transit, improving the passenger flow forecasting accuracy for new lines has gradually become a key focus in the rail transit industry. Therefore, it is necessary to evaluate, improve and optimize the traditional passenger flow forecasting methods for new lines.
［Method］
The newly launched metro lines in Wuhan are introduced. The trend pattern of passenger volume, and the comparison between the forecast and actual passenger flows on the new lines are analyzed. Based on passenger flow indicators such as line passenger volume, passenger flow volume of each station, and sectional passenger volume, the reasons for the passenger flow forecasting errors are analyzed, and improvement suggestions for the passenger flow forecasting method on new lines are put forward.
［Result & Conclusion］
Main reasons for the new line passenger flow forecasting errors include the limitation of the forecasting method itself, the insufficient consideration of line and station attribute, and the insufficient basic data for forecasting. The secondary reasons are the impact of the COVID-19 pandemic on passenger flow cultivation and insufficient consideration from the perspective of service. The methods to improve the accuracy of new line passenger flow forecasting include optimizing relevant forecasting parameters, strengthening the attribute analysis of different lines and stations by introducing correction coefficients and floating factors, strengthening the accumulation of basic urban traffic data and the analysis of passenger flow sensitivity, and exploring new methods for passenger flow forecasting of new lines or dynamically optimizing traditional forecasting methods.
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