Recent progress in taxi trajectory data mining

doi:10.11947/j.AGCS.2019.20190210

Abstract

Abstract: The development of big data technology, internet of thing and precise positioning has promoted the progress of city perception. The increasing taxi trajectory data not only records the pathway of taxis, but also implies the real-time traffic status, the information of urban dwellers' travel rule, urban structure and potential social problems. It is of great significance to mine and analyze the taxi trajectory data for smart transportation, urban planning etc. This paper reviews the field of taxi trajectory data analysis and applications in the past ten years. From the perspective of research methodology, four categories are identified:spatial statistical, time series analysis, graph and network analysis, and machine learning. Each category is reviewed with its current research situation, advantages disadvantages. Later on, applications, hot topics and future trends of taxi trajectory analysis are summarized to four areas including traffic management, resources and environmental protection, city planning, and human mobility. Finally, the current challenges and the future research directions in the field of taxi trajectory data mining are proposed.

Key words: trajectory data, data mining, taxi trajectory, review

CLC Number:

P208

WU Huayi, HUANG Rui, YOU Lan, XIANG Longgang. Recent progress in taxi trajectory data mining[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(11): 1341-1356.

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