Research on on-board fusion positioning system and accuracy correction algorithm in subway tunneling

doi:10.13474/j.cnki.11-2246.2024.0414

Abstract

Abstract: The “Metro Tunnel Safety Hidden Danger Comprehensive Inspection Vehicle” offers quick and accurate inspection of subway tunnel linings and potential hazards. Traditional positioning technologies in tunnels face issues like low accuracy and data sync problems due to complex underground and structural environments. To address this, a new on-board fusion positioning system with an accuracy correction algorithm has been developed. This system includes precise coded data and image acquisition, a fusion positioning algorithm, an accuracy correction algorithm, and a multi-source information coordinate conversion matrix.This fusion positioning system is more accurate than existing methods, capable of fast and dynamic positioning in both straight and curved tunnel sections. It achieves a positioning accuracy of 10 cm, with a relative error of less than or equal to 0.06% over up to 300 m in straight and 100 m in curved sections. The system's effectiveness and stability are confirmed by indoor and outdoor tests, making it a valuable tool for rapidly detecting and locating hidden safety hazards in subway tunnels, thereby enhancing tunnel safety.

Key words: subway tunnels, hazard detection, fusion positioning, accuracy correction, rapid detection

CLC Number:

LI Tianyu, XU Xianlei, ZHOU Donglin, WANG Hao, ZHANG Zhaotai. Research on on-board fusion positioning system and accuracy correction algorithm in subway tunneling[J]. Bulletin of Surveying and Mapping, 2024, 0(4): 83-89.

References

[1] 交通运输部.2023年6月城市轨道交通运营数据速报[N].中国交通报, 2023-07-11(002).
[2] ZONG Wenhao,ZHANG Changzhu,WANG Zhuping,et al.Architecture design and implementation of an autonomous vehicle[J].IEEE Access,2018,6: 21956-21970.
[3] GYAGENDA N,HATILIMA J V,ROTH H,et al.A review of GNSS-independent UAV navigation techniques[J].Robotics and Autonomous Systems,2022,152: 104069.
[4] 上官伟,谢朝曦,姜维.基于IMU标定补偿的列车组合定位优化方法[J].铁道学报,2020,42(2): 57-64.
[5] 房博乐,陈起金,牛小骥.轨道几何特征匹配列车定位方法[J].测绘通报,2019(10): 109-113.
[6] 吕一锋,陈淋.地铁运营隧道安全巡检系统及其应用[J].城市轨道交通研究,2014,17(10): 126-128.
[7] 张辰东,王兆瑞,金声震,等.基于SINS/RFID的隧道列车高精度定位方法[J].北京航空航天大学学报,2022,48(4): 632-638.
[8] SONG Xiang,LI Xu,TANG Wencheng,et al.A hybrid positioning strategy for vehicles in a tunnel based on RFID and in-vehicle sensors[J].Sensors,2014,14(12): 23095-23118.
[9] 许勇,邵浩东.UWB地铁轨道巡检车定位系统设计[J].机械设计与制造,2023,387(5): 138-140.
[10] 朱东飞,王永皎,杨烨,等.基于光栅阵列的城市轨道列车定位与测速方法[J].光子学报,2019,48(11): 159-166.
[11] JIANG Xuedong,LIU Zunmin,LIU Bilong,et al.Multi-sensor fusion for lateral vehicle localization in tunnels[J].Applied Sciences,2022,12(13): 6634.
[12] 曹泽强,孙英惠,洪琼,等.AprilTag图像识别应用于高差传递测量方法研究[J].测绘通报,2023(3): 27-32.
[13] WANG J,OLSON E.AprilTag 2: efficient and robust fiducial detection[C]//Proceedings of 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).[S.l.]:IEEE,2016: 4193-4198.
[14] GUO Zhenglong,FU Qiang,QUAN Quan.Pose estimation for multicopters based on monocular vision and AprilTag[C]//Proceedings of the 37th Chinese Control Conference (CCC).Wuhan:IEEE,2018: 4717-4722.
[15] ABBAS S M,ASLAM S,BERNS K,et al.Analysis and improvements in AprilTag based state estimation[J].Sensors,2019,19(24): 5480.