標題: | A Novel Method to Predict Traffic Features Based on Rolling Self-Structured Traffic Patterns |
作者: | Chiou, Yu-Chiun Lan, Lawrence W. Tseng, Chun-Ming 交大名義發表 運輸與物流管理系 註:原交通所+運管所 National Chiao Tung University Department of Transportation and Logistics Management |
關鍵字: | Rolling Self-Structured Traffic Patterns;Traffic Prediction;Growing Hierarchical Self-Organizing Map;Genetic Programming |
公開日期: | 2-十月-2014 |
摘要: | In this study, a novel method is proposed to predict the traffic features in a long freeway corridor with a number of time steps ahead. The proposed method, on the basis of rolling self-structured traffic patterns, utilizes the growing hierarchical self-organizing map model to partition the unlabeled traffic patterns into an appropriate number of clusters and then develops the genetic programming model for each cluster to predict its corresponding traffic features. For demonstration, the proposed method is tested against a 110-km freeway stretch, on which 48 time steps of 5-min traffic flows are predicted (i.e., a 4-h prediction). The prediction accuracy of the proposed method is compared with other models (ARIMA, SARIMA, and naive models) and the results support the superiority of the proposed method. Further analyses indicate that applications of the proposed method to larger scale freeway networks require sufficient lengths of observation to acquire enough traffic patterns for training and validation in order to achieve higher prediction accuracy. |
URI: | http://dx.doi.org/10.1080/15472450.2013.806764 http://hdl.handle.net/11536/25159 |
ISSN: | 1547-2450 |
DOI: | 10.1080/15472450.2013.806764 |
期刊: | JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS |
Volume: | 18 |
Issue: | 4 |
起始頁: | 352 |
結束頁: | 366 |
顯示於類別: | 期刊論文 |