The Prediction of Bus Speed Based on Kalman Filter

To solve the problem of traffic congestion, many cities have adopted a series of measures to develop public transportation. The bus speed is an important factor to measure the level of bus service, and it helps to determine the arrival time of bus, which can reduce the passengers’ anxiety and waiting time at bus stops. Kalman filter, whose mathematical structure is relatively simple, is a recursive solution to the discrete-data linear filter problem. It has the strengths of little calculation amount, low storage amount, high real-time characteristics. Therefore, this paper develops a prediction model of bus speed based on Kalman filter, gives a specific program to predict speed and verifies the model according to the real-time GPS measurements of No.84150 in Beijing on each Friday in March, 2013.The result shows that the proposed model has high accuracy and can be applied to the prediction of bus speed.