Spatiotemporal analysis of trajectory for a new real-time bus routes updated model

Abstract

With the development of location-based service, the wide range of applications of trajectory data obtained by GPS has made great contributions to the analysis of urban buses information. Affected by the increasing quantity of data, filtering out valid GPS trajectory data to update real-time information of urban buses faces new difficulties. In this study, a prototype model named Real-Time Bus Routes Updated model (RT-BRU) is developed to process and mine the GPS trajectory data collected from each urban bus of each interval. The main purpose of this model is to update real-time information of urban bus routes and provide much more realistic public navigation data with the help of trajectory data and geo-statistical tools. Compared to the regular algorithms and Chinese public navigation map data, the experiment results show that the RT-BRU model proposed here can discover more types of urban bus’s updated routes and play better in perspective of GPS points counts, operation time, calculation results, correct results and accuracy.