利用GPS轨迹的转向级交通拥堵精细分析

doi:10.11947/j.AGCS.2019.20170448

测绘学报 ›› 2019, Vol. 48 ›› Issue (1): 75-85.doi: 10.11947/j.AGCS.2019.20170448

利用GPS轨迹的转向级交通拥堵精细分析

唐炉亮¹, 阚子涵¹, 任畅¹, 张霞², 李清泉^1,3

1. 武汉大学测绘遥感信息工程国家重点实验室, 湖北武汉 430079;
2. 武汉大学城市设计学院, 湖北武汉 430072;
3. 深圳大学空间信息智能感知与服务深圳市重点实验室, 广东深圳 518060

收稿日期:2017-08-30 修回日期:2018-09-19 出版日期:2019-01-20 发布日期:2019-01-31
通讯作者: 阚子涵 E-mail:kzh@whu.edu.cn
作者简介:唐炉亮(1973-),男,博士,教授,博士生导师,研究方向为时空GIS、轨迹大数据分析与挖掘。E-mail:tll@whu.edu.cn
基金资助:
国家重点研发计划（2017YFB0503604；2016YFE0200400）；国家自然科学基金（41671442；41571430）

Fine-grained analysis of traffic congestions at the turning level using GPS traces

TANG Luliang¹, KAN Zihan¹, REN Chang¹, ZHANG Xia², LI Qingquan^1,3

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
2. School of Urban Design, Wuhan University, Wuhan 430072, China;
3. Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China

Received:2017-08-30 Revised:2018-09-19 Online:2019-01-20 Published:2019-01-31
Supported by:
The National Key Research and Development Program of China (Nos. 2017YFB0503604;2016YFE0200400);The National Natural Science Foundation of China (Nos. 41671442;41571430)

摘要/Abstract

摘要：

目前，基于GPS轨迹探测城市交通状态的研究缺乏对不同行驶方向的交通拥堵精细感知。针对此问题，本文提出一种基于出租车GPS轨迹的转向级交通拥堵事件探测方法。该方法首先在分析出租车运营行为特征的基础上，采用特征聚类方法滤选出能够反映真实交通状态的有效轨迹段；然后基于滤选后轨迹分析当前道路交通运行状态，探测城市路网中轻度、中度、重度3种不同强度的交通拥堵事件；最后基于拥堵事件轨迹分析交叉口不同转向的拥堵时间、拥堵强度和拥堵距离等转向级精细交通拥堵状态。试验结果表明，本文方法不仅能有效探测路网中不同强度的拥堵事件，而且能实现交叉口转向级拥堵事件的精细分析。

关键词: 交通拥堵, 转向级, 时空分析, GPS轨迹, 大数据

Abstract:

For the issue that existing approaches on studying traffic conditions using GPS traces lack of detailed analysis of traffic congestion, this paper puts forward an approach for detecting traffic congestion events based on taxis' GPS traces at turning level. Firstly, this approach analyzed taxis' operating patterns and filtered valid traces. Then this approach detected traffic congestion traces of three different intensities:mild congestion, moderate congestion and serious congestion, based on analyzing traffic conditions from the filtered valid trace segments. Finally, traffic flow speed, congestion time and congestion distance of each turning direction at an intersection were explored at a fine-grained level. The experimental results show that the proposed approach is able to detect congestions of different intensities and analyze congestion events at turning level.

Key words: traffic congestions, turning-level, space time analysis, GPS trace, big data

中图分类号:

P208

唐炉亮, 阚子涵, 任畅, 张霞, 李清泉. 利用GPS轨迹的转向级交通拥堵精细分析[J]. 测绘学报, 2019, 48(1): 75-85.

TANG Luliang, KAN Zihan, REN Chang, ZHANG Xia, LI Qingquan. Fine-grained analysis of traffic congestions at the turning level using GPS traces[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(1): 75-85.

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利用GPS轨迹的转向级交通拥堵精细分析

Fine-grained analysis of traffic congestions at the turning level using GPS traces

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