Journal of Positioning, Navigation, and Timing (J Position Navig Timing; JPNT)
Indexed in KCI (Korea Citation Index)
OPEN ACCESS, PEER REVIEWED
pISSN 2288-8187
eISSN 2289-0866

Correction-Dead Reckoning using Map Matching Information in an Underground Parking Lot

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CONTENTS

Research article

Citation: Seo, M. H., Kim, J., Park, S., & Suh, D. 2023, Correction-Dead Reckoning using Map Matching Information in an Underground Parking Lot, Journal of Positioning, Navigation, and Timing, 12, 391-398.

Journal of Positioning, Navigation, and Timing (J Position Navig Timing) 2023 December, Volume 12, Issue 4, pages 391-398. https://doi.org/10.11003/JPNT.2023.12.4.391

Received on 13 November 2023, Revised on 24 November 2023, Accepted on 01 December 2023, Published on 15 December 2023.

License: Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/bync/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Correction-Dead Reckoning using Map Matching Information in an Underground Parking Lot

Myung Hwan Seo†, Jeeseon Kim, Sojin Park, Dongkwon Suh

Hyundai AutoEver, 12, Teheran-ro 113-gil, Gangnam-gu, Seoul, Republic of Korea

†Corresponding Author: E-mail, myunghwan.seo@hyundai-autoever.com; Tel, +82-10-9177-7616

Abstract

In this paper, we propose a Correction Dead Reckoning (CDR) solution using correction information such as Map Matching FeedBack (MMFB) in an underground parking lot. In order to correct position errors in an underground parking lot, vehicle position and heading errors are corrected using MMFB information in road link properties. The proposed method was applied to an in-vehicle navigation system and tested. The experimental results show that the proposed robust dead reckoning solution corrects Dead Reckoning (DR) position errors that occur when driving for a long time in an underground parking lot.

Keywords

CDR, DR, MMFB, navigation system

References

Almansoub, Y. A. M., Zhong, M., Hu, Z., Huang, G., Alganess, M. A. A., et al. 2020, Multi-scale Vehicle Localization in Underground Parking Lots by Integration of Dead Reckoning, Wi-Fi and Vision, 6th International Conference on Big Data Computing and Communications (BIGCOM), Deqing, China, 24-25 July 2020, pp.41-49. https://doi.org/10.1109/BigCom51056.2020.00012

Dinh-Van, N., Nashashibi, F., Thanh-Huong, N., & Castelli, E. 2017, Indoor Intelligent Vehicle localization using WiFi received signal strength indicator, 2017 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM), Nagoya, Japan, 19-21 March 2017, pp.33-36. https://doi.org/10.1109/ICMIM.2017.7918849

Jia, Y., Jin, Z., Zhang, H., Li, Y., Wang, X., et al. 2019, Indoor Navigation for a Complex Parking Building Based on Computer Vision, 2019 5th International Conference on Transportation Information and Safety (ICTIS), Liverpool, UK, 14-17 July 2019, pp.183-190. https://doi.org/10.1109/ICTIS.2019.8883716

Kim, S.-T., Fan, M., Jung, S.-W., & Ko, S.-J. 2021, External Vehicle Positioning System Using Multiple FishEye Surveillance Cameras for Indoor Parking Lots,
IEEE Systems Journal, 15, 5107-5118. https://doi.org/10.1109/JSYST.2020.3019296

Kumar, A. K. T. R., Schäufele, B., Becker, D., Sawade, O., & Radusch, I. 2016, Indoor localization of vehicles using Deep Learning, 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), Coimbra, Portugal, 21-24 June 2016, pp.1-6. https://doi.org/10.1109/WoWMoM.2016.7523569

Lee, D., Min, K., & Kim, J. 2020, Wireless LAN-based Vehicle Location Estimation in GPS Shading Environment, The Journal of the Korea Institute of Intelligent Transport Systems, 19, 94-106. https://doi.org/10.12815/kits.2020.19.1.94

Park, W. J., Song, J. W., Kang, C. H., Lee, J. H., Seo, M. H., et al. 2019, MEMS 3D DR/GPS Integrated System for Land Vehicle Application Robust to GPS Outages,
IEEE Access, 7, 73336-73348. https://doi.org/10.1109/ACCESS.2019.2920095

Shin, B., Lee, J. H., Yu, C., Kim, C., & Lee, T. 2021, Underground Parking Lot Navigation System Using Long-Term Evolution Signal, Sensors, 21, 1725. https://
doi.org/10.3390/s21051725

Titterton, D. H. & Weston, J. L. 2004, Strapdown Inertial Navigation Technology, 2nd ed. (U.K.: IET)

Xi, L., Liu, Q., Li, M., & Liu, Z. 2007, Map Matching Algorithm and Its Application, Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007), Chengdu, China, 15-16 October 2007, pp.740-746. https://doi.org/10.2991/iske.2007.127

Zhao, J., Huang, Y., He, X., Zhang, S., Ye, C., et al. 2019, Visual Semantic Landmark-Based Robust Mapping and Localization for Autonomous Indoor Parking, Sensors, 19, 161. https://doi.org/10.3390/s19010161

Author contributIons

The Manuscript with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used “conceptualization, M.H.S.; methodology, M.H.S.; software, J.S.K.; validation, M.H.S., J.S.K. and S.J.P.; formal analysis, M.H.S.; investigation, D.K.S.; resources, J.S.K.; data curation, S.J.P.; writing—original draft preparation, M.H.S.; writing—review and editing, M.H.S.; visualization, J.S.K. and S.J.P.; supervision, M.H.S.; project administration, M.H.S.; funding acquisition, D.K.S.”. Authorship must be limited to those who have contributed substantially to the work reported.

Conflicts of interest

The authors declare no conflict of interest.