Recent progress in taxi trajectory data mining

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 rul...

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Main Authors: WU Huayi, HUANG Rui, YOU Lan, XIANG Longgang
Format: Article
Language:zho
Published: Surveying and Mapping Press 2019-11-01
Series:Acta Geodaetica et Cartographica Sinica
Subjects:
Online Access:http://html.rhhz.net/CHXB/html/2019-11-1341.htm
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spelling doaj-8d89df4d448e4911ba3fa323b85a357b2020-11-25T02:03:39ZzhoSurveying and Mapping PressActa Geodaetica et Cartographica Sinica1001-15951001-15952019-11-0148111341135610.11947/j.AGCS.2019.201902102019110210Recent progress in taxi trajectory data miningWU Huayi0HUANG Rui1YOU Lan2XIANG Longgang3State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, ChinaSchool of Computer Science and Information Engineering, Hubei University, Wuhan 430062, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, ChinaThe 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.http://html.rhhz.net/CHXB/html/2019-11-1341.htmtrajectory datadata miningtaxi trajectoryreview
collection DOAJ
language zho
format Article
sources DOAJ
author WU Huayi
HUANG Rui
YOU Lan
XIANG Longgang
spellingShingle WU Huayi
HUANG Rui
YOU Lan
XIANG Longgang
Recent progress in taxi trajectory data mining
Acta Geodaetica et Cartographica Sinica
trajectory data
data mining
taxi trajectory
review
author_facet WU Huayi
HUANG Rui
YOU Lan
XIANG Longgang
author_sort WU Huayi
title Recent progress in taxi trajectory data mining
title_short Recent progress in taxi trajectory data mining
title_full Recent progress in taxi trajectory data mining
title_fullStr Recent progress in taxi trajectory data mining
title_full_unstemmed Recent progress in taxi trajectory data mining
title_sort recent progress in taxi trajectory data mining
publisher Surveying and Mapping Press
series Acta Geodaetica et Cartographica Sinica
issn 1001-1595
1001-1595
publishDate 2019-11-01
description 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.
topic trajectory data
data mining
taxi trajectory
review
url http://html.rhhz.net/CHXB/html/2019-11-1341.htm
work_keys_str_mv AT wuhuayi recentprogressintaxitrajectorydatamining
AT huangrui recentprogressintaxitrajectorydatamining
AT youlan recentprogressintaxitrajectorydatamining
AT xianglonggang recentprogressintaxitrajectorydatamining
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