一种基于非参数回归的交通速度预测方法

doi:10.11896/j.issn.1002-137X.2016.02.047

摘要/Abstract

摘要： 非参数回归模型是近年来提出的一种交通状态预测模型。为进一步提高预测精度,基于非参数回归模型的特点,针对近邻状态的选取问题,提出了基于速度变化趋势和密集度的变K近邻精确搜索策略,对原有模型的近邻匹配方式进行了改进和优化,进而提出了一种短时交通平均速度预测模型。利用北京市浮动车系统数据对算法精度进行了验证,结果表明,该模型的预测精度优于基础的非参数回归和BP神经网络模型,并能为短时交通速度预测提供可行的结果。

关键词: 非参数回归,速度预测,短时交通状态

Abstract: Non-parametric regression model is a traffic forecasting model proposed in recent years.Based on the characteristics of the model,in order to improve the forecasting precision on the issue of neighboring states selection,the original neighbor matching was optimized by the classification of the trend of speed and varying K neighbors precise search strategy based on intensity,and then a short-term traffic speed forecasting model was proposed.Floating car data in Beijing was used in the experiments.Results show that the optimized model is better than normal non-parametric regression model and BP neural network model,and can provide practical speed for short-term traffic prediction.

Key words: Non-parametric regression,Speed forecasting,Short-term traffic state

史殿习,丁涛杰,丁博,刘惠. 一种基于非参数回归的交通速度预测方法[J]. 计算机科学, 2016, 43(2): 224-229. https://doi.org/10.11896/j.issn.1002-137X.2016.02.047

SHI Dian-xi, DING Tao-jie, DING Bo and LIU Hui. Traffic Speed Forecasting Method Based on Nonparametric Regression[J]. Computer Science, 2016, 43(2): 224-229. https://doi.org/10.11896/j.issn.1002-137X.2016.02.047

参考文献

[1] Zhu Yin,Wang Jun-li,Zhou Tong-mei.Introduction to Intelligent Transportation Systems[D].Beijing:People’s Public Security University of China Press,2007(in Chinese) 朱茵,王军利,周彤梅.智能交通系统导论[M].北京:中国人民公安大学出版社,2007
[2] Liu Le-min.The Short-term Traffic Flow Prediction of MainThoroughfares of City[D].Beijing:North China University of Technology,2013(in Chinese) 刘乐敏.城市主干道短时交通流预测研究[D].北京:北方工业大学,2013
[3] Van Lint H.Reliable travel time prediction for freeways[D].Netherlands:TRAIL Research School,2004
[4] Han C,Song S,Wang C H.A Real-time Short-term Traffic Flow Adaptive Forecasting Method Based on ARIMA Model[J].Acta Simulata Systematica Sinica,2004,6(7):1530-1456(in Chinese) 韩超,宋苏,王成红.基于 ARIMA 模型的短时交通流实时自适应预测[J].系统仿真学报,2004,16(7):1530-1532
[5] Sun S,Yu G,Zhang C.Short-term traffic flow forecasting using sampling Markov Chain method with incomplete data[C]∥Intelligent Vehicles Symposium,2004 IEEE.IEEE,2004:437-441
[6] Xie Y,Zhang Y,Ye Z.Short-Term Traffic Volume Forecasting Using Kalman Filter with Discrete Wavelet Decomposition[J].Computer-Aided Civil and Infrastructure Engineering,2007,22(5):326-334
[7] Nie P L, Yu Z,He Z C.Constrained Kalman filter combined predictor for short-term traffic flow[J].Journal of Traffic & Transportation Engineering,2008,8(5):86-90(in Chinese) 聂佩林,余志,何兆成.基于约束卡尔曼滤波的短时交通流量组合预测模型[J].交通运输工程学报,2008,8(5):86-90
[8] Jun G,Lin Q,Ming-yue L,et al.Forecasting urban traffic flow by SVR[C]∥2013 25th Chinese Control and Decision Confe-rence (CCDC).IEEE,2013:981-984
[9] Chen Xue-ping,Zeng Sheng,Hu Gang.Short-time Traffic Flow Prediction Based on BP Neural Network[J].T echnology of Highway and Transport,2008(3):115-117(in Chinese) 陈雪平,曾盛,胡刚.基于BP神经网络的短时交通流预测[J].公路交通技术,2008(3):115-117
[10] Zhang L,Rao Q,Yang W,et al.An Improved k-NN Nonparametric Regression-Based Short-Term Traffic Flow Forecasting Model for Urban Expressways[C]∥ICTE 2013:Safety,Speediness,Intelligence,Low-Carbon,Innovation.ASCE,2014:1214-1223
[11] Qu L,Lan S Y,Zhang J W.Short-term traffic forecasting based on nonparametric regression and floating car data[J].Computer Engineering & Design,2013,4(9):3298-3301(in Chinese) 屈莉,兰时勇,张建伟.基于浮动车数据非参数回归短时交通速度预测[J].计算机工程与设计,2013,34(9):3298-3301
[12] Gong Xiao-yan.Short-term Traffic Flow Forecasting and Routing based on Data Mining[D].Beijing:Institute of Automation of Chinese Academy of Sciences,2003(in Chinese) 宫晓燕.基于数据挖掘的短时交通流预测及辅助诱导[D].北京:中国科学院自动化研究所,2003
[13] Li S,Liu L J,Xie Y L.Chaotic prediction for short-term traffic flow of optimized BP neural network based on genetic algorithm[J].Control & Decision,2011,6(10):1581-1585(in Chinese) 李松,刘力军,解永乐.遗传算法优化 BP 神经网络的短时交通流混沌预测[J].控制与决策,2011,26(10):1581-1585
[14] Zheng W,Lee D H,Shi Q.Short-term freeway traffic flow prediction:Bayesian combined neural network approach[J].Journal of Transportation Engineering,2006,132(2):114-121
[15] He Wei.Research on Prediction of Traffic Flow Using Fuzzy Neural Networks[D].Lanzhou:Lanzhou Jiaotong University,2012(in Chinese) 何伟.模糊神经网络在交通流量预测中的应用研究[D].兰州:兰州交通大学,2012
[16] Zhang Xiao-li.A Study on Short-term Traffic Volume Forecasting Based on Non-Parametric Regression[D].Tianjin:Tianjin University,2007(in Chinese) 张晓利.基于非参数回归的短时交通流量预测方法研究[D].天津:天津大学,2007
[17] Li Zhen-long,Zhang Li-guo,Qian Hai-feng.Review of the Short-term Traffic Flow Forecasting Based on the Non-parametric Regression[J].Journal of Transportation Engineering and Information,2009,6(4):34-39(in Chinese) 李振龙,张利国,钱海峰.基于非参数回归的短时交通流预测研究综述[J].交通运输工程与信息学报,2009,6(4):34-39
[18] Guo F,Krishnan R,Polak J W.Short-term traffic prediction under normal and incident conditions using singular spectrum ana-lysis and the k-nearest neighbour method[C]∥IET and ITS Conference on Road Transport Information and Control (RTIC 2012).IET,2012:1-6
[19] Elfaouzi N E.Nonparametric traffic flow prediction using kernel estimator[C]∥Internaional symposium on transportation and traffic theory.1996:41-54

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