Abstract: The paper first analyzes the characteristic of predicting BRT vehicle travel time, and builds the prediction model. Then contraposed to the disadvantages of the tradition Kalman filter in predicting travel time, the paper presents an improved Kalman filter based on the fuzzy regression adaptive historical data samples of vehicle travel time. Finally the paper uses actual data collected from BRT Transport of South Axis Street in Beijing on Oct 9, 2008 for experiment. The results show that the improved filter effectively reduces the error of the original algorithm.

Key words: fuzzy regression, Kalman filter, travel time prediction