GPS has been widely used to track taxies in major cities. It is now possible to collect a large amount of taxi trajectory data over a long time period. With these data, we can gain insight into taxi drivers mobility pattern. One interesting problem is to investigate the taxi drivers mobility intelligence which is closely related to their income. Different taxi drivers may use different strategies to choose operating regions and work hours, find and select customers, and deliver customers to their destinations. In this paper, we present a comprehensive visual analysis system which can be used to analyze a large amount of spatial-temporal multi-dimensional trajectory data and identify some key factors that differentiate the top drivers and ordinary drivers according to their inco...[ Read more ]

GPS has been widely used to track taxies in major cities. It is now possible to collect a large amount of taxi trajectory data over a long time period. With these data, we can gain insight into taxi drivers mobility pattern. One interesting problem is to investigate the taxi drivers mobility intelligence which is closely related to their income. Different taxi drivers may use different strategies to choose operating regions and work hours, find and select customers, and deliver customers to their destinations. In this paper, we present a comprehensive visual analysis system which can be used to analyze a large amount of spatial-temporal multi-dimensional trajectory data and identify some key factors that differentiate the top drivers and ordinary drivers according to their income. We have used our system to analyze the trajectories of thousands of taxis in a major city and have gained some interesting findings on taxi drivers mobility intelligence.