Outdoor Hiking Navigation Road Network Map Construction Using Crowd-Source Trajectory Data

被引:0
|
作者
Tang, Jianbo [1 ,2 ]
Xia, Heyan [1 ]
Peng, Ju [1 ]
Hu, Zhiyuan [1 ]
Ding, Junjie [1 ]
Zhang, Yuyu [1 ]
机构
[1] School of Geosciences and Info-physics, Central South University, Changsha,410083, China
[2] Hunan Geospatial Information Engineering and Technology Research Center, Changsha,410007, China
基金
中国国家自然科学基金;
关键词
Air navigation - Highway administration - Information management - Motor transportation - Pedestrian safety - Risk management - Traffic control - Transportation routes;
D O I
10.12082/dqxxkx.2025.240479
中图分类号
学科分类号
摘要
[Objectives] The outdoor pedestrian navigation road network is a vital component of maps and a crucial basis for outdoor activity route planning and navigation. It plays a significant role in promoting outdoor travel development and ensuring safety management. However, existing research on road network generation mainly focuses on the construction of urban vehicular navigation networks, with relatively less emphasis on hiking navigation road networks in complex outdoor environments. Moreover, existing methods primarily emphasize the extraction of two-dimensional geometric information of roads, while the reconstruction of real three-dimensional geometric and topological structures remains underdeveloped. [Methods] To address these limitations, this study proposes a method for constructing the three-dimensional outdoor pedestrian navigation road network maps using crowdsourced trajectory data. This approach leverages a road network generation layer and an elevation extraction layer to extract the two-dimensional structure and three-dimensional elevation information of the road network. In the road network generation layer, a trajectory density stratification strategy is adopted to construct the two-dimensional vector road network. In the elevation extraction layer, elevation estimation and optimization are performed to generate an elevation grid raster map, which is then matched with the two-dimensional road network to produce the three-dimensional hiking navigation road network. [Results] To demonstrate the effectiveness of the proposed approach, experiments were conducted using 1 170 outdoor trajectories collected in 2021 from Yuelu Mountain Scenic Area in Changsha through an online outdoor website. The constructed outdoor three-dimensional hiking road network map achieved an average positional offset of 4.201 meters in two-dimensional space and an average elevation estimation error of 7.656 meters. The results demonstrate that the proposed method effectively handles outdoor trajectory data with high noise and varied trajectory density distribution differences, generating high-quality three-dimensional hiking road network maps. [Conclusions] Compared to traditional outdoor two-dimensional road networks, the three-dimensional navigation road networks constructed this study provide more comprehensive and accurate map information, facilitating improved pedestrian path planning and navigation services in complex outdoor environments. © 2025 Science Press. All rights reserved.
引用
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页码:151 / 166
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