Skip to main content
SpringerLink
Log in

Cooperative vehicle-infrastructure localization based on the symmetric measurement equation filter

  • Published:
GeoInformatica Aims and scope Submit manuscript

Abstract

Precise and accurate localization is important for safe autonomous driving. Given a traffic scenario which has multiple vehicles equipped with internal sensors for self-localization, and external sensors from the infrastructure for vehicle localization, vehicle-infrastructure communication can be used to improve the accuracy and precision of localization. However, as the number of vehicles in a scenario increases, associating measurement data with the correct source becomes increasingly challenging. We propose a solution utilizing the symmetric measurement equation filter (SME) for cooperative localization to address data association issue, as it does not require an enumeration of measurement-to-target associations. The principal idea is to define a symmetrical transformation which maps measurements to a homogeneous function, thereby effectively addressing several challenges in vehicle-infrastructure scenarios such as data association, bandwidth limitations and registration/configuration of the external sensor. To the best of our knowledge, the proposed solution is among the first to address all these issues of cooperative localization simultaneously, by utilizing the topology information of the vehicles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Tian F, Wu C, Chu D, Sun C, Zhou T (2014) Experimental design of integrated platform for demonstration of cooperative vehicle infrastructure systems in china. In: 2014 IEEE 17th International Conference on Intelligent Transportation Systems (ITSC), pp 105–108. doi:10.1109/ITSC.2014.6957674

  2. Boasman N, Clarke D, Davison S, Stokes R Advanced test methods for integrated navigation systems, Royal Institute of Navigation

  3. Laneurit J, Chapuis R, Chausse F (2005) Accurate vehicle positioning on a numerical map. Int J Control Autom Syst 3(1):15–31

    Google Scholar 

  4. Zhang F, Staehle H, Chen G, Buckl C, Knoll A (2013) Multiple vehicle cooperative localization under random finite set framework. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

  5. Chan Lan K, Huang C-M, Tsai C-Z (2008) On the locality of vehicle movement for vehicle-infrastructure communication. In: 8th International Conference on ITS Telecommunications, ITST 2008, pp 116–120. doi:10.1109/ITST.2008.4740240

  6. Roumeliotis S, Rekleitis I (2003) Analysis of multirobot localization uncertainty propagation. In: Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, (IROS 2003), vol 2, pp 1763–1770. doi:10.1109/IROS.2003.1248899

  7. Fox D, Burgard W, Thrun S (1999) Markov localization for mobile robots in dynamics environments. J Artif Intell Res 11:391–427

    Google Scholar 

  8. Howard A, Matark M, Sukhatme G (2002) Localization for mobile robot teams using maximum likelihood estimation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1, pp 434–439. doi:10.1109/IRDS.2002.1041428

  9. Nerurkar E, Roumeliotis S, Martinelli A (2009) Distributed maximum a posteriori estimation for multi-robot cooperative localization. In: IEEE International Conference on Robotics and Automation, ICRA ’09, pp 1402–1409. doi:10.1109/ROBOT.2009.5152398

  10. Kamen E (1992) Multiple target tracking based on symmetric measurement equations. IEEE Trans Autom Control 37(3):371–374. doi:10.1109/9.119640

    Article  Google Scholar 

  11. Zhang F, Hinz G, Clarke D, Knoll A (2015) Vehicle-infrastructure localization based on the sme filter. In: 2015 IEEE 18th International Conference on Connected Vehicles and Cooperative Systems Workshop, Intelligent Transportation Systems (ITSC)

  12. Swati, Bhaumik S (2012) Multiple target tracking using homogeneous symmetric measurement. In: 2012 1st International Conference on Recent Advances in Information Technology (RAIT), pp 707–712. doi:10.1109/RAIT.2012.6194581

  13. Kamen E, Sastry C (1993) Multiple target tracking using products of position measurements. IEEE Trans Aerosp Electron Syst 29(2):476–493. doi:10.1109/7.210085

    Article  Google Scholar 

  14. Karam N, Chausse F, Aufrere R, Chapuis R (2006) Cooperative multi-vehicle localization. In: Intelligent Vehicles Symposium, 2006 IEEE, pp 564–570. doi:10.1109/IVS.2006.1689688

  15. Li H, Nashashibi F (2012) Cooperative multi-vehicle localization using split covariance intersection filter. In: Intelligent Vehicles Symposium (IV), 2012 IEEE, pp 211–216. doi: 10.1109/IVS.2012.6232155, (to appear in print)

  16. Roumeliotis S, Bekey G (2002) Distributed multirobot localization. IEEE Trans Robot Autom 18(5):781–795. doi:10.1109/TRA.2002.803461

    Article  Google Scholar 

  17. Karam N, Chausse F, Aufrere R, Chapuis R (2006) Localization of a group of communicating vehicles by state exchange. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 519–524. doi:10.1109/IROS.2006.282028

  18. SADA (2015) Smart Adaptive Data Aggregation, BMWi, IKT fur Elektromobilitat III. http://www.projekt-sada.de

  19. Fortmann TE, Bar-Shalom Y, Scheffe M (1983) Sonar tracking of multiple targets using joint probabilistic data association. IEEE J Ocean Eng 8(3):173–184. doi:10.1109/JOE.1983.1145560

    Article  Google Scholar 

  20. Mahler R (2003) Multitarget bayes filtering via first-order multitarget moments. IEEE Trans Aerosp Electron Syst 39(4):1152–1178. doi:10.1109/TAES.2003.1261119

    Article  Google Scholar 

  21. Giannopoulos E, Streit R, Swaszek P (1996) Probabilistic multi-hypothesis tracking in a multi-sensor, multi-target environment. In: Data Fusion Symposium, 1996. ADFS ’96., First Australian, pp 184–189. doi:10.1109/ADFS.1996.581104

  22. Leven W, Lanterman A (2009) Unscented kalman filters for multiple target tracking with symmetric measurement equations. IEEE Trans Autom Control 54(2):370–375. doi:10.1109/TAC.2008.2008327

  23. Leven WF, Lanterman AD (2004) Multiple target tracking with symmetric measurement equations using unscented kalman and particle filters. In: Proceedings of the Thirty-Sixth Southeastern Symposium on System Theory, 2004, pp 195–199. doi:10.1109/SSST.2004.1295647

  24. Baum M, Hanebeck U (2013) The kernel-sme filter for multiple target tracking. In: 2013 16th International Conference on Information Fusion (FUSION), pp 288–295

  25. Li X, Jilkov V (2003) Survey of maneuvering target tracking. part i. dynamic models. IEEE Trans Aerosp Electron Syst 39(4):1333–1364. doi:10.1109/TAES.2003.1261132

    Article  Google Scholar 

  26. Daum FE (1991) Cramer-rao bound for multiple-target tracking. In: Proc. SPIE, Vol. 1481, pp 341–344. doi:10.1117/12.45667

  27. Kamen EW, Lee YJ, Sastry CR (1994) Parallel sme filter for tracking multiple targets in three dimensions. In: Proc. SPIE, Vol. 2235, pp 417–428. doi:10.1117/12.179068

Download references

Acknowledgments

This work is partially supported by the SADA project funded by the German ministry of economics (BMWi), within the program ‘IKT für Elektromobilität III’.

Author information

Authors and Affiliations

  1. Fortiss GmbH, Guerickestr. 25, 80805, München, Germany

    Feihu Zhang, Gereon Hinz & Dhiraj Gulati

  2. Cranfield University, Cranfield, United Kingdom

    Daniel Clarke

  3. Institute of Robotics and Embedded Systems, Technische Universität München, 85748, Garching bei München, Germany

    Alois Knoll

Authors
  1. Feihu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gereon Hinz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dhiraj Gulati
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Daniel Clarke
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alois Knoll
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Feihu Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, F., Hinz, G., Gulati, D. et al. Cooperative vehicle-infrastructure localization based on the symmetric measurement equation filter. Geoinformatica 20, 159–178 (2016). https://doi.org/10.1007/s10707-016-0244-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10707-016-0244-3

Keywords

Search

Navigation