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Multi-step Ahead Link Travel Time Prediction using Data Fusion  

Lee, Young-Ihn (서울대학교 환경대학원)
Kim, Sung-Hyun (한국건설기술연구원)
Yoon, Ji-Hyeon (서울대학교 환경대학원)
Publication Information
Journal of Korean Society of Transportation / v.23, no.4, 2005 , pp. 71-79 More about this Journal
Abstract
Existing arterial link travel time estimation methods relying on either aggregate point-based or individual section-based traffic data have their inherent limitations. This paper demonstrates the utility of data fusion for improving arterial link travel time estimation. If the data describe traffic conditions, an operator wants to know whether the situations are going better or worse. In addition, some traffic information providing strategies require predictions of what would be the values of traffic variables during the next time period. In such situations, it is necessary to use a prediction algorithm in order to extract the average trends in traffic data or make short-term predictions of the control variables. In this research. a multi-step ahead prediction algorithm using Data fusion was developed to predict a link travel time. The algorithm performance were tested in terms of performance measures such as MAE (Mean Absolute Error), MARE(mean absolute relative error), RMSE (Root Mean Square Error), EC(equality coefficient). The performance of the proposed algorithm was superior to the current one-step ahead prediction algorithm.
Keywords
통행시간예측;데이터융합;다주기 통행시간예측;칼만 필터링;교통정보;
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  • Reference
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