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http://dx.doi.org/10.12652/Ksce.2019.39.3.0461

Frequent Origin-Destination Sequence Pattern Analysis from Taxi Trajectories  

Lee, Tae Young (Chosun University)
Jeon, Seung Bae (Chosun University)
Jeong, Myeong Hun (Chosun University)
Choi, Yun Woong (Chosun University College of Sience& Technology)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.39, no.3, 2019 , pp. 461-467 More about this Journal
Abstract
Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.
Keywords
Clustering analysis; Sequence pattern analysis; Origin-destination analysis; Movement data;
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