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The prediction of passenger flow distribution for urban rail transit based on multi-factor model

机译:基于多因素模型的城市轨道交通客流分配预测

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摘要

The lack of the historical data of new rail line makes the passenger flow distribution prediction be a challenge. Traditional methods always use simple factors, which can not reflect the complexity of OD distribution. This paper proposes a novel passenger flow distribution prediction method based on multi-factor model. This method obtains quantitative impact factors of OD distribution by analyzing the historical data of existing stations, and then constructs the multi-factor model. The model considers the influence of the nature of the station, as well as the impact of rail network structure, which makes it more precision. Validation experiment results show that the model is reasonable.
机译:缺乏新铁路的历史数据使得客流分布预测成为一个挑战。传统方法始终使用简单的因素,无法反映OD分布的复杂性。提出了一种基于多因素模型的新型客流分配预测方法。该方法通过分析现有台站的历史数据来获得OD分布的定量影响因子,然后构建多因子模型。该模型考虑了车站性质的影响以及铁路网结构的影响,使其更加精确。验证实验结果表明该模型是合理的。

著录项

  • 来源
  • 会议地点 Singapore(SG)
  • 作者单位

    Beijing Transportation Information Center, Beijing Key Laboratory of Integrated Traffic Operation Surveillance and Service, Beijing, P. R. China;

    Beijing Transportation Information Center, Beijing Key Laboratory of Integrated Traffic Operation Surveillance and Service, Beijing, P. R. China;

    Beijing Transportation Information Center, Beijing Key Laboratory of Integrated Traffic Operation Surveillance and Service, Beijing, P. R. China;

    Beijing Transportation Information Center, Beijing Key Laboratory of Integrated Traffic Operation Surveillance and Service, Beijing, P. R. China;

    Beijing Transportation Information Center, Beijing Key Laboratory of Integrated Traffic Operation Surveillance and Service, Beijing, P. R. China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Data models; Correlation; Predictive models; Rails; Roads; Computational modeling; Mathematical model;

    机译:数据模型;相关性;预测模型;铁路;道路;计算模型;数学模型;

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