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GNSS-only Collaborative Positioning Among Connected Vehicles

Published:02 July 2019Publication History

ABSTRACT

Cooperative positioning is considered a key strategy for the improvement of localization and navigation performance in harsh contexts such as urban areas. Modern communication paradigms can support the exchange of inter-vehicle ranges measured from on-board sensors or obtained through Global Satellite Navigation System (GNSS) measurements. The paper presents an overview of the GNSS-only collaborative localization in the context of cooperative connected cars. It provides an experimental example along with new results about the tight integration of collaboratively-generated inter-vehicle relative measurements collected by a target vehicle by means of a double differentiation w.r.t. to a set of five aiding vehicles. An average improvement of the positioning accuracy of about 11% motivates the research effort towards multi-agent connected positioning systems.

References

  1. M. A. Caceres, F. Penna, H. Wymeersch, and R. Garello. 2011. Hybrid Cooperative Positioning Based on Distributed Belief Propagation. IEEE Journal on Selected Areas in Communications 29, 10 (December 2011), 1948--1958.Google ScholarGoogle ScholarCross RefCross Ref
  2. F. De Ponte Müller. 2017. Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles. Sensors 17, 2 (2017).Google ScholarGoogle Scholar
  3. F. de Ponte Müller, E. M. Diaz, B. Kloiber, and T. Strang. 2014. Bayesian cooperative relative vehicle positioning using pseudorange differences. In 2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014. 434--444.Google ScholarGoogle Scholar
  4. F. De Ponte Müller, A. Steingass, and T. Strang. 2013. Zero-Baseline Measurements for Relative Positioning in Vehicular Environments. In 6th European Workshop on GNSS Signals and Signal Processing. https://elib.dlr.de/86457/Google ScholarGoogle Scholar
  5. F. Dovis, C. Chiasserini, L. Musumeci, and C. Borgiattino. 2014. Context-aware peer-to-peer and cooperative positioning. In International Conference on Localization and GNSS 2014 (ICL-GNSS 2014). 1--6.Google ScholarGoogle ScholarCross RefCross Ref
  6. D. A. Grejner-Brzezinska, C. K. Toth, T. Moore, J. F. Raquet, M. M. Miller, and A. Kealy. 2016. Multisensor Navigation Systems: A Remedy for GNSS Vulnerabilities? Proc. IEEE 104, 6 (June 2016), 1339--1353.Google ScholarGoogle ScholarCross RefCross Ref
  7. E. D. Kaplan and C. Hegarty. 2017. Understanding GPS/GNSS: Principles and applications. Artech House. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. K. Liu, H. B. Lim, E. Frazzoli, H. Ji, and V. C. S. Lee. 2014. Improving Positioning Accuracy Using GPS Pseudorange Measurements for Cooperative Vehicular Localization. IEEE Transactions on Vehicular Technology 63, 6 (July 2014), 2544--2556.Google ScholarGoogle ScholarCross RefCross Ref
  9. A. Martinelli, F. Pont, and R. Siegwart. 2005. Multi-Robot Localization Using Relative Observations. In Proceedings of the 2005 IEEE International Conference on Robotics and Automation. 2797--2802.Google ScholarGoogle Scholar
  10. C. Mensing and J. J. Nielsen. 2010. Centralized cooperative positioning and tracking with realistic communications constraints. In 2010 7th Workshop on Positioning, Navigation and Communication. 215--223.Google ScholarGoogle Scholar
  11. A. Minetto, C. Cristodaro, and F. Dovis. 2017. A collaborative method for positioning based on GNSS inter agent range estimation. In 2017 25th European Signal Processing Conference (EUSIPCO). 2714--2718.Google ScholarGoogle Scholar
  12. A. Minetto and F. Dovis. 2018. A theoretical framework for collaborative estimation of distances among GNSS users. In 2018 IEEE/ION Position, Location and Navigation Symposium (PLANS). 1492--1501.Google ScholarGoogle Scholar
  13. A. Minetto, A. Nardin, and F. Dovis. 2018. Tight Integration of GNSS Measurements and GNSS-based Collaborative Virtual Ranging. In 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+2018). 2399--2413.Google ScholarGoogle Scholar
  14. E. D. Nerurkar and S. I. Roumeliotis. 2010. Asynchronous Multi-Centralized Cooperative Localization. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. 4352--4359.Google ScholarGoogle Scholar
  15. P. Papadimitratos, A. D. La Fortelle, K. Evenssen, R. Brignolo, and S. Cosenza. 2009. Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation. IEEE Communications Magazine 47, 11 (November 2009), 84--95.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. M. Rohani, D. Gingras, V. Vigneron, and D. Gruyer. 2015. A New Decentralized Bayesian Approach for Cooperative Vehicle Localization Based on Fusion of GPS and VANET Based Inter-Vehicle Distance Measurement. IEEE Intelligent Transportation Systems Magazine 7, 2 (Summer 2015), 85--95.Google ScholarGoogle ScholarCross RefCross Ref
  17. S. I. Roumeliotis and G. A. Bekey. 2000. Collective localization: a distributed Kalman filter approach to localization of groups of mobile robots. In Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), Vol. 3. 2958--2965 vol.3.Google ScholarGoogle ScholarCross RefCross Ref
  18. M. Tahir, S. S. Afzal, M. S. Chughtai, and K. Ali. 2019. On the Accuracy of Inter-Vehicular Range Measurements Using GNSS Observables in a Cooperative Framework. IEEE Transactions on Intelligent Transportation Systems 20, 2 (Feb 2019), 682--691.Google ScholarGoogle ScholarCross RefCross Ref

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              cover image ACM Conferences
              TOP-Cars '19: Proceedings of the 1st ACM MobiHoc Workshop on Technologies, mOdels, and Protocols for Cooperative Connected Cars
              July 2019
              46 pages
              ISBN:9781450368070
              DOI:10.1145/3331054

              Copyright © 2019 ACM

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              Publication History

              • Published: 2 July 2019

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