基于神经网络的海量GPS数据交通流量预测
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摘要
交通流量数据具有非周期性、非线性和随机性等特点.为了更准确地对未设置ETC路段交通流量进行预测,采取相应措施处理交通拥堵问题,提出了基于神经网络推论模型为主体的交通流量预测系统.通过实验验证了ARIMA乘积季节模型、BP神经网络和RBF神经网络的多种训练函数的预测精度及适应性.相对于常规预测方法,基于神经网络的预测方法具有更好的适应性,而且预测精度也更高.
Traffic flow data is characterized by non-periodicity, nonlinearity and randomness. In order to accurately predict the traffic flow without ETC, it take measures to solve the traffic jam problem quickly and accurately, a traffic flow prediction system is proposed based on a neural network inference model. It is verified the prediction accuracy and adaptability of the ARIMA seasonal model, BP neural networks and RBF neural networks with various training functions by experiments. Relative to conventional forecasting method, the prediction method which is based on neural network is more adaptability and prediction accuracy is higher than conventional forecasting method.
Traffic flow data is characterized by non-periodicity, nonlinearity and randomness. In order to accurately predict the traffic flow without ETC, it take measures to solve the traffic jam problem quickly and accurately, a traffic flow prediction system is proposed based on a neural network inference model. It is verified the prediction accuracy and adaptability of the ARIMA seasonal model, BP neural networks and RBF neural networks with various training functions by experiments. Relative to conventional forecasting method, the prediction method which is based on neural network is more adaptability and prediction accuracy is higher than conventional forecasting method.
引文
[1]张崇娇.城市交通流量预测及控制策略研究[D].太原:中北大学,2018.Zhang C J.Research on urban traffic flow forecast and control strategies[D].Taiyuan:North University of China,2018.
[2]Liang Z,Wakahara Y.City traffic prediction based on real-time traffic information for Intelligent Transport Systems[C].International Conference on ITS Telecommunications,IEEE,2013:378-383.
[3]Rivero C R,Pati?o H D,Pucheta J A.Short-term rainfall time series prediction with incomplete data[C].IEEE International Joint Conference on Neural Networks,2015:1-6.
[4]Lu H,Zhang A J.Improved adaptive Kalman filtering algorithm for vehicular positioning[C].Control Conference,IEEE,2015:5 125-5 129.
[5]Yang L C,Jia L,Wang H.Wavelet network with genetic algorithm and its applications for traffic flow forecasting[C].Fifth World Congress on Intelligent Control and Automation,Conference Proceedings,2004:5 330-5 333.
[6]Smith B L,Williams B M,Oswald R K.Comparison of parametric and nonparametric models for traffic flow forecasting[J].Transportation Research Part C Emerging Technologies,2002,10(4):303-321.DOI:10.1016/S0968-090X(02)00009-8.
[7]Zhang Y P,Pei Y D.Research on traffic flow forecasting model based on cusp catastrophe theory[J].Journal of Harbin Institute of Technology,2004,24(1):1-5.
[8]Xu H C,Daniel J D.Realtimeighway traffic simulation and prediction using inductance loop data[C].Proceedings of the Vehicle Navigation and Information Systems Conference,1995:194-199.
[9]Lin W H.A Gaussian maximum likelihood formulation for short-term forecasting of traffic flow[C].IEEE Conference on Intelligent Transportation Systems,PSC,2001:150-155
[10]Sun S L,Yu G Q,Zhang C S.Short-term traffic flow forecasting using sampling Markov Chain method with incomplete data[C].Proceedings,IEEE Intelligent Vehicles Symposium,2004:437-441.
[11]Voort M V D,Dougherty M,Watson S.Combining kohonen maps with arima time series models to forecast traffic flow[J].Transportation Research Part C Emerging Technologies,1996,4(5):307-318.DOI:10.1016/S0968-090X(97)82903-8.
[12]Chang S C,Kim R S,Kim S J,et al.Traffic-flow forecasting using a 3-stage model[C].Proceedings of the IEEE,Intelligent Vehicles Symposium,2002:451-456.
[13]Yuan Z Z,Li W Y,Liu H D.Forecast of dynamic traffic flow[C].Proceedings of the Conference on Traffic and Transportation Studies,ICTT S,2000:507-512.
[14]Chen H,Grant-Muller S.Use of sequential learning for short-term traffic flow forecasting[J].Transportation Research Part C Emerging Technologies,2001,9(5):319-336.DOI:10.1016/S0968-090X(00)00039-5.
[15]Chen S Y,Qu G F,Wang X H,et al.Traffic flow forecasting based on grey neural network model[C].International Conference on Machine Learning and Cybernetics,2003:1 275-1 278.
[16]谢军,吴伟,杨晓光.用于短时交通流量预测的多项式分布滞后模型[J].同济大学学报:自然科学版,2011,39(9):1 297-1 302.Xie J,Wu W,Yang X.A PDL model used for shortterm traffic flow forecasting[J].Journal of Tongji University,2011,39(9):1 297-1 302.
[17]赵亚萍,张和生,周卓楠,等.基于最小二乘支持向量机的交通流量预测模型[J].北京交通大学学报,2011,35(2):114-117.Zhao Y,Zhang H,Zhou Z,et al.Model of traffic volume forecasting based on least squares support vector machine[J].Journal of Beijing Jiaotong University,2011,35(2):114-117.
[18]Castillo E,Menéndez J M,Sánchez-Cambronero S.Predicting traffic flow using Bayesian networks[J].Transportation Research Part B Methodological,2008,42(5):482-509.DOI:10.1016/j.trb.2007.10.003.
[19]Song G J,Hu C,Xie K Q,et al.Process neural network modeling for real time short-term traffic flow prediction[J].Journal of Traffic&Transportation Engineering,2009,9(5):73-77.
[20]Tang H,Liang Y,Huang Z,et al.Key technology of real-time road navigation method based on intelligent data eesearch[J].Computational Intelligence and Neuroscience,2016:1-16.
[21]Cheng T X,Du W B,Chen J Z.A short-term combination forecasting model for traffic flow based on the BPneural network[J].Applied Mechanics&Materials,2013,255:1339-1344.
[22]曹虹.基于BP神经网络的交通流量预测[D].西安:长安大学,2012Cao H,Traffic flow prediction based on BP neural network[D].Xi'an:Chang'an University,2012.
[23]申慧,刘知贵,李春菊.基于BP神经网络的交通流量预测设计[J].西南科技大学学报,2008,23(2):72-75.DOI:10.3969/j.issn.1671-8755.2008.02.016.Shen H,Liu Z G,Li C J.Research on traffic flow forecasting design based on BP neural network[J].Journal of Southwest University of Science and Technology,2008,23(2):72-75.
[24]尚宁,覃明贵,王亚琴,等.基于BP神经网络的路口短时交通流量预测方法[J].计算机应用与软件,2006,23(2):32-33.DOI:10.3969/j.issn.1000-386X.2006.02.015.Shang N,Qin M G,Wang Y Q,et al.A BP neural network method for short-term traffic flow forecasting on crossroads[J].Computer Applications and Software,2006,23(2):32-33.
[2]Liang Z,Wakahara Y.City traffic prediction based on real-time traffic information for Intelligent Transport Systems[C].International Conference on ITS Telecommunications,IEEE,2013:378-383.
[3]Rivero C R,Pati?o H D,Pucheta J A.Short-term rainfall time series prediction with incomplete data[C].IEEE International Joint Conference on Neural Networks,2015:1-6.
[4]Lu H,Zhang A J.Improved adaptive Kalman filtering algorithm for vehicular positioning[C].Control Conference,IEEE,2015:5 125-5 129.
[5]Yang L C,Jia L,Wang H.Wavelet network with genetic algorithm and its applications for traffic flow forecasting[C].Fifth World Congress on Intelligent Control and Automation,Conference Proceedings,2004:5 330-5 333.
[6]Smith B L,Williams B M,Oswald R K.Comparison of parametric and nonparametric models for traffic flow forecasting[J].Transportation Research Part C Emerging Technologies,2002,10(4):303-321.DOI:10.1016/S0968-090X(02)00009-8.
[7]Zhang Y P,Pei Y D.Research on traffic flow forecasting model based on cusp catastrophe theory[J].Journal of Harbin Institute of Technology,2004,24(1):1-5.
[8]Xu H C,Daniel J D.Realtimeighway traffic simulation and prediction using inductance loop data[C].Proceedings of the Vehicle Navigation and Information Systems Conference,1995:194-199.
[9]Lin W H.A Gaussian maximum likelihood formulation for short-term forecasting of traffic flow[C].IEEE Conference on Intelligent Transportation Systems,PSC,2001:150-155
[10]Sun S L,Yu G Q,Zhang C S.Short-term traffic flow forecasting using sampling Markov Chain method with incomplete data[C].Proceedings,IEEE Intelligent Vehicles Symposium,2004:437-441.
[11]Voort M V D,Dougherty M,Watson S.Combining kohonen maps with arima time series models to forecast traffic flow[J].Transportation Research Part C Emerging Technologies,1996,4(5):307-318.DOI:10.1016/S0968-090X(97)82903-8.
[12]Chang S C,Kim R S,Kim S J,et al.Traffic-flow forecasting using a 3-stage model[C].Proceedings of the IEEE,Intelligent Vehicles Symposium,2002:451-456.
[13]Yuan Z Z,Li W Y,Liu H D.Forecast of dynamic traffic flow[C].Proceedings of the Conference on Traffic and Transportation Studies,ICTT S,2000:507-512.
[14]Chen H,Grant-Muller S.Use of sequential learning for short-term traffic flow forecasting[J].Transportation Research Part C Emerging Technologies,2001,9(5):319-336.DOI:10.1016/S0968-090X(00)00039-5.
[15]Chen S Y,Qu G F,Wang X H,et al.Traffic flow forecasting based on grey neural network model[C].International Conference on Machine Learning and Cybernetics,2003:1 275-1 278.
[16]谢军,吴伟,杨晓光.用于短时交通流量预测的多项式分布滞后模型[J].同济大学学报:自然科学版,2011,39(9):1 297-1 302.Xie J,Wu W,Yang X.A PDL model used for shortterm traffic flow forecasting[J].Journal of Tongji University,2011,39(9):1 297-1 302.
[17]赵亚萍,张和生,周卓楠,等.基于最小二乘支持向量机的交通流量预测模型[J].北京交通大学学报,2011,35(2):114-117.Zhao Y,Zhang H,Zhou Z,et al.Model of traffic volume forecasting based on least squares support vector machine[J].Journal of Beijing Jiaotong University,2011,35(2):114-117.
[18]Castillo E,Menéndez J M,Sánchez-Cambronero S.Predicting traffic flow using Bayesian networks[J].Transportation Research Part B Methodological,2008,42(5):482-509.DOI:10.1016/j.trb.2007.10.003.
[19]Song G J,Hu C,Xie K Q,et al.Process neural network modeling for real time short-term traffic flow prediction[J].Journal of Traffic&Transportation Engineering,2009,9(5):73-77.
[20]Tang H,Liang Y,Huang Z,et al.Key technology of real-time road navigation method based on intelligent data eesearch[J].Computational Intelligence and Neuroscience,2016:1-16.
[21]Cheng T X,Du W B,Chen J Z.A short-term combination forecasting model for traffic flow based on the BPneural network[J].Applied Mechanics&Materials,2013,255:1339-1344.
[22]曹虹.基于BP神经网络的交通流量预测[D].西安:长安大学,2012Cao H,Traffic flow prediction based on BP neural network[D].Xi'an:Chang'an University,2012.
[23]申慧,刘知贵,李春菊.基于BP神经网络的交通流量预测设计[J].西南科技大学学报,2008,23(2):72-75.DOI:10.3969/j.issn.1671-8755.2008.02.016.Shen H,Liu Z G,Li C J.Research on traffic flow forecasting design based on BP neural network[J].Journal of Southwest University of Science and Technology,2008,23(2):72-75.
[24]尚宁,覃明贵,王亚琴,等.基于BP神经网络的路口短时交通流量预测方法[J].计算机应用与软件,2006,23(2):32-33.DOI:10.3969/j.issn.1000-386X.2006.02.015.Shang N,Qin M G,Wang Y Q,et al.A BP neural network method for short-term traffic flow forecasting on crossroads[J].Computer Applications and Software,2006,23(2):32-33.