基于众源轨迹数据的行人路网提取

doi:10.13474/j.cnki.11-2246.2021.0080

测绘通报 ›› 2021, Vol. 0 ›› Issue (3): 69-74.doi: 10.13474/j.cnki.11-2246.2021.0080

基于众源轨迹数据的行人路网提取

郑恬静^1,2,3, 黄金彩^1,3, 周宝定^1,2,3, 张德津^3,4

1. 深圳大学土木与交通工程学院, 广东深圳 518060;
2. 深圳大学城市智慧交通与安全运维研究院, 广东深圳 518060;
3. 深圳大学广东省城市空间信息工程重点实验室, 广东深圳 518060;
4. 深圳大学建筑与城市规划学院, 广东深圳 518060

收稿日期:2020-05-25 出版日期:2021-03-25 发布日期:2021-04-02
通讯作者: 周宝定。E-mail:bdzhou@szu.edu.cn
作者简介:郑恬静(1996—),女,硕士,主要研究方向为智能交通。E-mail:1810333006@email.szu.edu.cn
基金资助:
国家自然科学基金（41701519）；深圳市科技计划（JCYJ20180305125058727）；广东省基础与应用基础研究基金（2019A1515011910）；深圳市孔雀团队项目（KQTD20180412181337494）；国家重点研发计划（2019YFB2102703）

Pedestrian road network extraction based on crowdsourcing trajectory data

ZHENG Tianjing^1,2,3, HUANG Jincai^1,3, ZHOU Baoding^1,2,3, ZHANG Dejin^3,4

1. College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China;
2. Institute of Urban Smart Transportation & Safety Maintenance, Shenzhen University, Shenzhen 518060, China;
3. Guangdong Key Laboratory of Urban Informatics, Shenzhen University, Shenzhen 518060, China;
4. College of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China

Received:2020-05-25 Online:2021-03-25 Published:2021-04-02

摘要/Abstract

摘要： 目前，导航位置服务应用提供的路线大多基于机动车道路网数据，难以满足行人导航的需求，有无完备的行人道路网络成为制约行人导航应用的重要因素，因此，本文提出了一种基于莫尔斯理论的行人路网提取方法。首先对轨迹进行预处理，清除轨迹数据中的冗余和噪声，并对原始轨迹进行合理分割，形成清晰的轨迹集合；然后利用莫尔斯理论，对步行轨迹密度图中的“山脊线”进行提取，并重构步行道路网。试验分析时采用深圳大学校园步行GPS轨迹数据进行行人路网提取，通过将提取的行人路网结果与OpenStreetMap（OSM）数据进行定性和定量比较，验证本文方法的有效性；同时通过与当前典型的路网提取方法进行对比分析发现，本文方法能提取出高质量的行人路网。

关键词: 道路提取, 步行轨迹, 轨迹预处理, 行人路网, 莫尔斯理论

Abstract: At present, the routes provided by the navigation location service application are mostly based on the data of the vehicle road network, which is difficult to meet the needs of pedestrian navigation. The complete pedestrian network has become an important factor restricting the application of pedestrian navigation. Therefore, this paper proposes a pedestrian network extraction method based on Morse theory. First, the trajectory is preprocessed to remove redundancy and noise in the trajectory data, and the original trajectory is divided reasonably to form a clear trajectory set. Secondly, Morse theory is used to extract the "ridgeline" in the density map of walking track and reconstruct the pedestrian network. The experimental analysis uses the walking GPS track data of Shenzhen university campus to extract the pedestrian network. By qualitative and quantitative comparison of the extracted pedestrian network results with OpenStreetMap (OSM) data, the effectiveness of the method in this paper is verified. At the same time, compared with the current typical road network extraction methods, the proposed method can extract high quality pedestrian network.

Key words: road extraction, walking trajectory, trajectory preprocessing, pedestrian network, Morse theory

中图分类号:

P228

郑恬静, 黄金彩, 周宝定, 张德津. 基于众源轨迹数据的行人路网提取[J]. 测绘通报, 2021, 0(3): 69-74.

ZHENG Tianjing, HUANG Jincai, ZHOU Baoding, ZHANG Dejin. Pedestrian road network extraction based on crowdsourcing trajectory data[J]. Bulletin of Surveying and Mapping, 2021, 0(3): 69-74.

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基于众源轨迹数据的行人路网提取

Pedestrian road network extraction based on crowdsourcing trajectory data

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