| Summary: | 碩士 === 國立交通大學 === 資訊管理研究所 === 102 === In recent years, the development of intelligent transportation systems (ITS) has become more and more popular. Real-time traffic information services of ITS draw much attention. These services are offered based on the collection of traffic information. Traffic information can be estimated and collected by collecting and analyzing the historical cellular network data. Most studies focused on traffic information estimation of highway. However, highway only has one direction, whereas local road has multiple directions. The study of traffic estimation of local road is an interesting research issue. In this thesis, a directed positioning algorithm based on cellular network data for local traffic is proposed to collect the cellular network signals and record the cell identities (IDs) along with the timestamps of these signals. Data mining technique is used to analyze these IDs and timestamps, and subsequently determine the road segments on which vehicles are. In experiments, three different factors are considered: connected cell IDs, cell order, and cell residence time. The results show that the proposed algorithm has the best performance whenever all three factors are considered. With all three factors considered, the effectiveness of the proposed algorithm is improved by 13% compared to previous studies.
|
|---|
