k-Nearest Neighbor Model for Multiple-Time-Step Prediction of Short-Term Traffic Condition
作者： Bin Yu , Xiaolin Song , Feng Guan , Zhiming Yang , Baozhen Yao
DOI: 10.1061/(ASCE)TE.1943-5436.0000816
关键词: Data mining 、 Traffic generation model 、 Artificial neural network 、 k-nearest neighbors algorithm 、 Traffic flow 、 Real-time data 、 Intelligent transportation system 、 Term (time) 、 Support vector machine 、 Engineering
摘要: AbstractOne of the most critical functions an intelligent transportation system (ITS) is to provide accurate and real-time prediction traffic condition. This paper develops a short-term condition model based on k-nearest neighbor algorithm. In model, time-varying continuous characteristic flow considered, multi-time-step proposed single-time-step model. To test accuracy GPS data taxis in Foshan city, China, are used. The results show that with spatial-temporal parameters provides good performance compared support vector machine (SVM) artificial neural network (ANN) real-time-data history-data also appear indicate effective approach predicting
sci-hub.se 参考文章(29)
Daniel Boto-Giralda, Francisco J. Díaz-Pernas, David González-Ortega, José F. Díez-Higuera, Míriam Antón-Rodríguez, Mario Martínez-Zarzuela, Isabel Torre-Díez, Wavelet‐Based Denoising for Traffic Volume Time Series Forecasting with Self‐Organizing Neural Networks Computer-aided Civil and Infrastructure Engineering. ,vol. 25, pp. 530- 545 ,(2010) , 10.1111/J.1467-8667.2010.00668.X
Byoungjo Yoon, Hyunho Chang, Potentialities of Data-Driven Nonparametric Regression in Urban Signalized Traffic Flow Forecasting Journal of Transportation Engineering-asce. ,vol. 140, pp. 04014027- ,(2014) , 10.1061/(ASCE)TE.1943-5436.0000662
Howard R. Kirby, Susan M. Watson, Mark S. Dougherty, Should we use neural networks or statistical models for short-term motorway traffic forecasting? International Journal of Forecasting. ,vol. 13, pp. 43- 50 ,(1997) , 10.1016/S0169-2070(96)00699-1
Wanli Min, Laura Wynter, Real-time road traffic prediction with spatio-temporal correlations Transportation Research Part C-emerging Technologies. ,vol. 19, pp. 606- 616 ,(2011) , 10.1016/J.TRC.2010.10.002
Bin Yu, Zhong-Zhen Yang, Kang Chen, Bo Yu, Hybrid Model for Prediction of Bus Arrival Times at Next Station Journal of Advanced Transportation. ,vol. 44, pp. 193- 204 ,(2010) , 10.1002/ATR.136
Wangmeng Zuo, David Zhang, Kuanquan Wang, On kernel difference-weighted k -nearest neighbor classification Pattern Analysis and Applications. ,vol. 11, pp. 247- 257 ,(2008) , 10.1007/S10044-007-0100-Z
Ruimin Li, Geoffrey Rose, Incorporating uncertainty into short-term travel time predictions Transportation Research Part C-emerging Technologies. ,vol. 19, pp. 1006- 1018 ,(2011) , 10.1016/J.TRC.2011.05.014
Yiannis Kamarianakis, Poulicos Prastacos, Forecasting Traffic Flow Conditions in an Urban Network: Comparison of Multivariate and Univariate Approaches: Transportation Research Record. ,vol. 1857, pp. 74- 84 ,(2003) , 10.3141/1857-09
Michael J. Demetsky, Brian L. Smith, Multiple-Interval Freeway Traffic Flow Forecasting: Transportation Research Record. ,vol. 1554, pp. 136- 141 ,(1996) , 10.3141/1554-17
Rod E. Turochy, Enhancing Short-Term Traffic Forecasting with Traffic Condition Information Journal of Transportation Engineering-asce. ,vol. 132, pp. 469- 474 ,(2006) , 10.1061/(ASCE)0733-947X(2006)132:6(469)