Traffic phenomena are associated with a complex dynamic behavior of spatiotemporal traffic patterns. It is possible to understand the features of real traffic by a spatiotemporal analysis approach for real measured traffic data. In this paper, a space-time visualization analysis method is designed and carried out for taxi spatiotemporal dataset from Beijing floating car data acquisition system and Beijing GIS data. Through this method, large-amount taxi GPS data is processed and the spatial–temporal trajectory is analyzed. And then taxi daily operation time, operating range and residence location of individual driver, vehicle operation and rest periods and other indicators are calculated, which are important characteristic parameters of Beijing Taxi Operations. In sum, continuous, comprehensive, and dynamic analysis information for monitoring taxi operation status can be acquired through the method. These information can provide the decision basis for city taxi operation management , and help to improve the city taxi operation management level.
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Zhang et al. (2015) studied this question.
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