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基于计算实验的城市道路行程时间预测与建模

唐少虎 刘小明 陈兆盟 张金金

唐少虎, 刘小明, 陈兆盟, 张金金. 基于计算实验的城市道路行程时间预测与建模. 自动化学报, 2015, 41(8): 1516-1527. doi: 10.16383/j.aas.2015.c140846
引用本文: 唐少虎, 刘小明, 陈兆盟, 张金金. 基于计算实验的城市道路行程时间预测与建模. 自动化学报, 2015, 41(8): 1516-1527. doi: 10.16383/j.aas.2015.c140846
TANG Shao-Hu, LIU Xiao-Ming, CHEN Zhao-Meng, ZHANG Jin-Jin. Urban Road Travel Time Prediction and Modeling via Computational Experiments. ACTA AUTOMATICA SINICA, 2015, 41(8): 1516-1527. doi: 10.16383/j.aas.2015.c140846
Citation: TANG Shao-Hu, LIU Xiao-Ming, CHEN Zhao-Meng, ZHANG Jin-Jin. Urban Road Travel Time Prediction and Modeling via Computational Experiments. ACTA AUTOMATICA SINICA, 2015, 41(8): 1516-1527. doi: 10.16383/j.aas.2015.c140846

基于计算实验的城市道路行程时间预测与建模

doi: 10.16383/j.aas.2015.c140846
基金项目: 

国家自然科学基金(61374191), 国家科技支撑计划(2014BAG03B01)资助

详细信息
    作者简介:

    刘小明 北方工业大学电气与控制工程学院教授.2004年获得中国科学院自动化所博士学位.主要研究方向为交通流理论,智能交通控制.E-mail:tslxm@sina.com

Urban Road Travel Time Prediction and Modeling via Computational Experiments

Funds: 

Supported by National Natural Science Foundation of China (61374191) and National Science and Technology Support Program (2014BAG03B01)

  • 摘要: 城市道路行程时间预测对于提高交通管控效果具有重要意义. 本文综合应用平行系统、集散波、误差反馈修正、多模型自适应控制及模型库动态优 化策略等方法与技术对间断流行程时间预测问题进行了研究. 首先,介绍了平行系统理论的基本原理及计算实验的基本方法; 然后,给出了基于平行系统理论的路段行程时间的预测模型, 设计了基于集散波的行程时间计算实验方法, 提出了多模型自适应行程时间预测并给出了模型动态优化策略. 最后,通过实验证明了本方法的有效性. 结果表明, 本文方法预测精度较高, 且能够对行程时间预测值进行持续优化, 可为后续的间断流行程时间预测研究提供借鉴.
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出版历程
  • 收稿日期:  2014-12-04
  • 修回日期:  2015-04-28
  • 刊出日期:  2015-08-20

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