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城市道路交通流短时预测及可靠性分析

聂庆慧 夏井新 钱振东

聂庆慧, 夏井新, 钱振东. 城市道路交通流短时预测及可靠性分析[J]. 西南交通大学学报, 2013, 26(5): 955-960. doi: 10.3969/j.issn.0258-2724.2013.05.027
引用本文: 聂庆慧, 夏井新, 钱振东. 城市道路交通流短时预测及可靠性分析[J]. 西南交通大学学报, 2013, 26(5): 955-960. doi: 10.3969/j.issn.0258-2724.2013.05.027
NIE Qinghui, XIA Jingxin, QIAN Zhendong. Short-Term Traffic Flow Forecasting and Reliability Analysis of Urban Road[J]. Journal of Southwest Jiaotong University, 2013, 26(5): 955-960. doi: 10.3969/j.issn.0258-2724.2013.05.027
Citation: NIE Qinghui, XIA Jingxin, QIAN Zhendong. Short-Term Traffic Flow Forecasting and Reliability Analysis of Urban Road[J]. Journal of Southwest Jiaotong University, 2013, 26(5): 955-960. doi: 10.3969/j.issn.0258-2724.2013.05.027

城市道路交通流短时预测及可靠性分析

doi: 10.3969/j.issn.0258-2724.2013.05.027
基金项目: 

国家科学自然基金资助项目(51108079)

Short-Term Traffic Flow Forecasting and Reliability Analysis of Urban Road

  • 摘要: 为了捕捉交通流随机波动导致的交通流短时预测的不确定性,利用反映预测波动的异方差对可靠性进行量化预测;基于时间序列及其异方差理论,构建了以单整自回归滑动平均ARIMA(0,1,1)模型为均值方程的城市道路交通流短时预测的广义自回归条件异方差GARCH(1,1)模型. 通过ARCH LM检验证实,GARCH(1,1)模型能够有效捕捉并消除ARIMA(0,1,1)模型的异方差性.结果表明:基于GARCH(1,1)模型的城市快速路流量预测的MAPE值不高于10%,城市快速路及主干道速度预测的MAPE值为7.86%~10.24%;与ARIMA(0,1,1)模型预测的固定置信区间相比,在自由流交通状况下,GARCH(1,1)模型在有效预测前提下的预测置信区间更窄;在交通拥挤状况下,GARCH(1,1)模型能够通过放大预测置信区间宽度减少无效预测.

     

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出版历程
  • 收稿日期:  2012-06-28
  • 刊出日期:  2013-10-25

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