| 出租车轨迹数据挖掘进展 |
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| 引用本文： | 吴华意,黄蕊,游兰,向隆刚.出租车轨迹数据挖掘进展[J].测绘学报,2019,48(11):1341-1356. |
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| 作者姓名： | 吴华意 黄蕊 游兰 向隆刚 |
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| 作者单位： | 武汉大学测绘遥感信息工程国家重点实验室,湖北武汉,430072;湖北大学计算机与信息工程学院,湖北武汉,430062 |
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| 基金项目： | 国家自然科学基金（41771474） |
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| 摘 要： | 大数据、物联网与精密定位技术的发展推动了城市感知的进步。随着社会活动的与日俱增,出租车轨迹数据不仅记录了出租车的行车轨迹,还蕴藏着道路交通状态、城市居民出行规律、城市结构及其他社会问题。通过各种数据分析与挖掘手段对出租车轨迹数据进行深入探究,对于智能交通、城市规划等有着重要意义。本文综述了近十年国内外基于出租车轨迹大数据的相关研究,按照空间统计方法、时间序列方法、图论与网络方法及机器学习方法等4类,详细阐述各类方法的研究现状。随后,本文分析了现有研究的应用领域、热点主题和发展趋势。最后,本文指出了出租车轨迹数据挖掘研究领域面临的挑战和未来研究方向。
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| 关 键 词： | 轨迹数据 数据挖掘 出租车轨迹 综述 |
| 收稿时间： | 2019-05-27 |
| 修稿时间： | 2019-08-30 |
Recent progress in taxi trajectory data mining |
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| 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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| Authors: | WU Huayi HUANG Rui YOU Lan XIANG Longgang |
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| Institution: | 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China;2. School of Computer Science and Information Engineering, Hubei University, Wuhan 430062, China |
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| 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. |
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