Indoor and outdoor integrated pedestrian network construction based on crowdsourced data

Acta Geodaetica et Cartographica Sinica

HUANG Jincai¹  LI Qingquan²  ZHANG Wenxiang³  ZHOU Baoding³ 

[1] Big Data Institute, Central South University, Changsha 410083, China;College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China;Institute of Urban Smart Transportation & Safety Maintenance, Shenzhen University, Shenzhen 518060, China;

关键词: crowdsourcing geospatial data;    pedestrian navigation;    pedestrian network;    indoor and outdoor integration;    morse theor;   

DOI  :  10.11947/j.AGCS.2022.20210276

来源: DOAJ

【 摘 要 】

The integrity and accuracy of the pedestrian road network is the key to ensuring pedestrian navigation services. Most of the current pedestrian road networks are constructed based on outdoor road facilities, lacking data support for indoor walkable paths, and cannot provide accurate and true optimal path planning services in navigation applications. In view of this, this article proposes a method for constructing an integrated indoor and outdoor pedestrian road network based on crowd-sourced data. It uses crowd-sourced trajectories recorded by smartphone positioning sensors and inertial sensors. The missing or drifting indoor walking data is first filtered, and then used the improved pedestrian dead reckoning (PDR) method calculates accurate indoor trajectories, and then uses Morse theory to generate a complete pedestrian road network covering indoor and outdoor pedestrian paths. In the experimental analysis, the pedestrian road network was constructed on the collected 260 walking trajectory data, and the real road network data was collected by high-precision measurement equipment for comparative analysis, and the experimental results were comprehensively evaluated with the Open Street Map data. Experimental results show that the method in this paper can accurately and completely generate an integrated indoor and outdoor pedestrian road network.

【 授权许可】

Unknown