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13 October 2022 Research on calculation methods of taxi passenger volume based on satellite positioning data
Yun Xiao, Meng Zhang, Rongqiao Li, Zijun Liang
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Proceedings Volume 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022); 122870X (2022) https://doi.org/10.1117/12.2640759
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 2022, Wuhan, China
Abstract
Scientific measurement of taxi passenger volume is of great significance for optimizing urban traffic. In this paper, based on the satellite positioning data of taxis in Huangshan City, the identification method of taxi passenger trips is studied with Python as the analysis tool, and the taxi passenger trip trajectory is extracted. Through the sampling survey, the passenger load factor of different periods is calculated, based on which the distribution characteristics of taxis under different time and space is analyzed and visualized through ArcGIS and TransCAD. The research demonstrates that the average daily passenger volume of taxis in Huangshan City is 14,013 person-times, and the number of taxi passengers on rest days is higher than that on working days, and significantly higher during the day than at night; taxi trips are mainly distributed in the main urban areas of the city, accounting for 87.36% of the total trips, forming two passenger corridors, east-west and north-south.
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Yun Xiao, Meng Zhang, Rongqiao Li, and Zijun Liang "Research on calculation methods of taxi passenger volume based on satellite positioning data", Proc. SPIE 12287, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2022), 122870X (13 October 2022); https://doi.org/10.1117/12.2640759
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KEYWORDS
Satellites
Data conversion
Analytical research
Statistical analysis
Data analysis
Visual analytics
Visualization
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