Bus Travel-Time Prediction with a Forgetting Factor

Abstract

Bus travel-time prediction has drawn a lot of research interests in previous literature. This paper proposes a prediction model for bus travel time based on the support vector machine (SVM) regression method. A forgetting factor is introduced to assign the weight to the recent data resulting from the bus running time–based variable quantities. The Grubbs’ test method is applied to remove outliers from the input data. The proposed model is assessed with the data of transit route number 23 in the city of Dalian, China. Results show that the SVM with the forgetting factor and the Grubbs’ test method is a powerful tool for bus travel-time prediction.