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基于向量误差修正模型的短时交通参数预测

, PP. 1076-1081

Keywords: 交通运输系统工程,向量误差修正模型,交通参数,短时预测

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Abstract:

为了进一步提高短时交通参数预测的精度,针对交通参数之间存在的内在相关性,在对各交通参数时间序列进行平稳性检验、协整检验的基础上,构建了一种适应于短时交通参数预测的多变量时间序列模型-向量误差修正模型,并对模型的稳定性进行了检验。最后,利用上海市南北高架快速路的感应线圈实测数据进行了实验验证和对比分析。实验结果表明,所构建的向量误差修正模型具有较好的预测效果,能够进一步降低短时交通参数预测的误差。

References

[1]  Williams B M. Multivariate vehicular traffic flow prediction: an evaluation of ARIMAX modeling[C]∥The Transportation Research Board Annual Meeting, Washington D C, 2001.
[2]  杨兆升,王媛,管青. 基于支持向量机方法的短时交通流量预测方法[J].吉林大学学报:工学版,2006,36(6):881-884. Yang Zhao-sheng, Wang Yuan, Guan Qing. Short-time traffic prediction method based on SVM[J]. Journal of Jilin University(Engineering and Technology Edition), 2006,36(6):881-884.
[3]  周小鹏,冯奇,孙立军. 基于最近邻法的短时交通流预测[J]. 同济大学学报:自然科学版,2006,34(10):1494-1498. Zhou Xiao-peng, Feng Qi, Sun Li-jun. Short-term traffic flow forecasting based on nearest neighbor algorithm[J]. Journal of Tongji University(Nature Science), 2006,34(10):1494-1498.
[4]  龚勃文,林赐云,李静,等. 基于核自组织映射-前馈神经网络的交通流短时预测[J]. 吉林大学学报:工学版,2011,41(4):938-942. Gong Bo-wen, Lin Ci-yun, Li Jing, et al. Short-time traffic flow prediction based on KSOM-BP neural network[J]. Journal of Jilin University(Engineering and Technology Edition), 2011,41(4):938-942.
[5]  樊娜,赵祥模,戴明,等. 短时交通流预测模型[J]. 交通运输工程学报,2012,12(4):114-119. Fan Na, Zhao Xiang-mo, Dai Ming, et al. Short-term traffic flow prediction model[J]. Journal of Traffic and Transportation Engineering, 2012, 12(4):114-119.
[6]  常刚,张毅,姚丹亚. 基于时空依赖性的区域路网短时交通流预测模型[J].清华大学学报:自然科学版,2013,53(2):215-221. Chang Gang, Zhang Yi, Yao Dan-ya. Short-time traffic flow forecasting model for regional road network based on spatial-temporal dependency[J]. Journal of Tsinghua University(Science and Technology), 2013, 53(2): 215-221.
[7]  高为,陆百川,贠天鹂,等. 基于时空特性和RBF神经网络的短时交通流预测[J]. 交通信息与安全,2011,29(1):16-24. Gao Wei, Lu Bai-chuan, Yun Tian-li, et al. Short-term traffic flow forecasting based on spatiotemporal characteristics of traffic flow and RBF neural network[J].Journal of Transportation Information and Safety, 2011,29(1):16-24.
[8]  Mina W, Wynterb L. Real road traffic prediction with spatio-temporal correlation[J]. Transportation Research Part C, 2011, 19(4): 606-616.
[9]  Stathopoulos A, Karlaftis M G. A multivariate state space approach for urban traffic flow modeling and prediction[J]. Transportation Research Part C, 2003,11(2):121-135.
[10]  万莉敏. 我国燃料油期货市场有效性研究[D]. 哈尔滨:哈尔滨工程大学,2010. Wan Li-min. The study on efficiency of Chinese fuel oil futures market[D]. Harbin: Harbin Engineering University,2010.
[11]  俞立平,潘云涛,武夷山. 工业化与信息化互动关系的实证研究[J]. 中国软科学,2009(1):34-40. Yu Li-ping, Pan Yun-tao, Wu Yi-shan. Study on relationship between industrialization and information[J]. China Soft Science Magazine, 2009(1): 34-40.

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