Adjacent Total Average Algorithm for Travel Time Prediction

Travel time prediction plays an important role with the development of ATIS (Advanced Travelers Information Systems).It provides useful information which may allow travelers to change their routes and to decide whether or not to make necessary changes to their routes or departure times. Here we proposed a new method ATA(Adjacent total average). The challenge of this paper is to provide accurate travel time to compare with others method .With the use of same set of historical travel time and comparing the previous results of other four methods like Successive Moving Average (SMA), Naive Bayesian Classification (NBC) method, Switching method and K -means Clustering(MKC) Our algorithms exhibit high accuracy in predicting travel time.