Abstract
Floating Car Data (FCD) has been analyzed for various purposes in past years. However, limited research about the behaviors of taking long-distance taxi rides has been made available. In this paper, we used data from over 12,000 taxis during a six-month period in Shanghai to analyze the spatiotemporal patterns of long-distance taxi trips. We investigated these spatiotemporal patterns by comparing them with metro usage in Shanghai, in order to determine the extent and how the suburban trains divert the passenger flow from taxis. The results identified 12 pick-up and six drop-off hotspots in Shanghai. Overall, the pick-up locations were relatively more concentrated than the drop-off locations. Temporal patterns were also revealed. Passengers on long-distance taxi rides were observed to avoid the rush hours on the street as their first priority and tried to avoid the inconvenience of interchanges on the metro lines as their second priority.
Highlights
In an increasing number of cities, taxis are equipped with mobile devices for recording positions and for the provision of services
Using the P and R indices, we evaluated the probability of long distance taxi rides and the proportion of workdays and non-workdays for each hotspot
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Summary
In an increasing number of cities, taxis are equipped with mobile devices for recording positions and for the provision of services. Li et al [9] tried to determine the best strategies for taxi drivers to pick up passengers at a given time and location, based on the FCD data analysis, with 5500 taxis in Hangzhou, China. As a type of movement data, FCD has been used for mining and understanding human mobility in urban areas. We analyzed FCD data in Shanghai from a different point view compared to the existing approaches. The main conclusions are derived and summarized in the last section
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