Bus arrival time prediction model based on support vector machine and Kalman filter

Authors presented the bus arrival time prediction model based on support vector machine (SVM) and Kalman filter technique. The SVM which had three input features including: Time-of-day, weather and segment was used to predict the baseline of bus running time from historical trip data. Applying the newest bus running information, combined with baseline time of SVM input, Kalman filter was used to predict bus arrival time dynamically. Bus arrival time forecasted by the proposed model was assessed with the data of transit route number 7 in Dalian Economic and Technological Development Zone in China. Results show that the model is a powerful tool for bus arrival time prediction.