Abstract
This research investigates a type of connection between passengers from trajectory data tracked in smart card automatic fare collection systems. Such connection is present if two passengers share trajectories with exact the same spatiotemporal footprints, and its presence implies that focal passengers practically accompany one another on their whole journeys. The connection yields social networks that potentially improve understandings in human mobility because the simultaneous spatial and temporal proximities between those passengers further imply common travel demand and similar mobility pattern. We demonstrate how to extract such connections and then how to build social networks by providing detailed algorithms and performing them on a field data set. Significant time variance is observed regarding different time points or time durations. Evolution of network structures in consecutive fixed-width time windows and in increasing time durations is also illustrated.
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Acknowledgement
The authors acknowledge partial financial support from the National Natural Science Foundation of China under Grant 71572155 and from the Science & Technology Department of Sichuan Province under Grant 2017JY0225.
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Geng, W., Zhang, D. (2020). Weaving Social Networks from Smart Card Data: An On-Journey-Accompanying Approach. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. Automated Driving and In-Vehicle Experience Design. HCII 2020. Lecture Notes in Computer Science(), vol 12212. Springer, Cham. https://doi.org/10.1007/978-3-030-50523-3_18
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DOI: https://doi.org/10.1007/978-3-030-50523-3_18
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