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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Surveying and Mapping Press
2019-11-01
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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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