Analysis of Travel Time Patterns in Urban Using Taxi GPS Data

Travel time is the basic information to city life. Accurate travel time information can help people plan travel schedule and improve work efficiency. This paper proposes a method to discover travel-time patterns which can evaluate the travel efficiency in the city. The travel time data is based on the trajectories extracted from taxi GPS data. First we propose a method to recognize popular paths between origin-destination pairs, and cluster the same trajectories together meanwhile the abnormal trajectories are discarded. We treat the travel time data as time series, and Weighted Moving Average (WMA) is used to extract the normal travel time pattern. In the final part of the paper, the model is validated through the taxi GPS data of Beijing. We recognize different travel time patterns and some real examples of different paths are analyzed.