Abstract: A detection system and related algorithms of distributed trip behaviors are developed to identify charac-teristics of trips in urban rail transit systems using Wi-Fi information collected from passengers.The unique Media Access Control(MAC)addresses of mobile devices carried by passengers can be detected by detection devices installed in stations and be uploaded to a data center.The characteristics of route choices and travel time can be identified by comparing time stamps and related station IDs of selected mobile devices in the data center.T ransfer time can also be obtained by consid-ering operation time of the urban rail transit system,w hich can be utilized as a constraint of route identification.A case study of the rail transit system in Xi′an with actual information from the AFC data indicates that the proposed system can identify route choices and travel time for all kinds of networks with a sampling rate of 32.86% and an error rate of 3.8%. Analyzing the results of this system can be utilized for precise management,such as ticket clearing and station design.