Abstract:The statistical characteristics of taxi behavior have important significance to study the economic and psychological of human dynamics. Based on the taxi GPS track data in Xi'an, the lane-changing behavior was quantitatively studied by big data analysis technology. The model of a lane-changeing behavior recognition was designed, combined with the big data analysis technology, the number of taxi drivers' lane-changing was quantified in terms of different time periods, and the correlation analysis between taxi drivers' lane-changing times, taxi average driving speed, and taxi drivers' income was carried out. The results show that there is a significant negative correlation between the income of taxi drivers and the average driving speed of taxis, which further indicates that taxi drivers' habits and psychology have a significant impact on the whole taxi operation.