Skip to main content

Estimating Position Relation between Two Pedestrians Using Mobile Phones

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7319))

Abstract

In a complex indoor environment such as a huge station in an urban area, sometimes the direction and distance relative to another person are more important for pedestrians than their absolute positions, e.g. to search for a lost child. We define this information as the position relation. Our goal is to develop a position relation estimation method on a mobile phone with built-in motion sensors. In literature, methods of cooperative navigation using two pedestrians’ positions estimated by pedestrian dead reckoning and a range sensor have been proposed. However, these methods cannot be applied to a mobile phone because pedestrian dead reckoning does not work well when a mobile phone is in a bag, and because there is no range sensor in a phone. In fact, no Bluetooth is reliable as a substitute range sensor. This paper proposes another approach to estimate the position relation of pedestrians. Our method finds the timing when two pedestrians are in close proximity to each other and walk together by using Bluetooth as a proximity sensor and corrects the parameters of position updates dynamically, even if absolute positions are unknown. The algorithm and evaluation results are presented in this paper.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Google Latitude, http://www.google.com/latitude

  2. Kourogi, M., Sakata, N., Okuma, T., Kurata, T.: Indoor/Outdoor Pedestrian Navigation with an Embedded GPS/RFID/Self-contained Sensor System. In: Pan, Z., Cheok, D.A.D., Haller, M., Lau, R., Saito, H., Liang, R. (eds.) ICAT 2006. LNCS, vol. 4282, pp. 1310–1321. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Mezentsev, O., Lachapelle, G., Collin, J.: Pedestrian Dead Reckoning – A Solution to Navigation in GPS Signal Degraded Areas. Geomatica 59(2), 175–182 (2005)

    Google Scholar 

  4. Fischer, C., Gellersen, H.: Location and Navigation Support for Emergency Responders: A Survey. Pervasive Computing, 38–47 (2010)

    Google Scholar 

  5. Frank, K., Krach, B., Catterall, N., Robertson, P.: Development and Evaluation of a Combined WLAN & Inertial Indoor Pedestrian Positioning System. ION GNSS (2009)

    Google Scholar 

  6. Fang, L., Antsaklis, P.J., Montestruque, L.A., McMickell, M.B., Lemmon, M., Sun, Y., Fang, H., Koutroulis, I., Haenggi, M., Xie, M., Xie, X.: Design of a Wireless Assisted Pedestrian Dead Reckoning System - The NavMote Experience. IEEE Trans. IMS 54, 2342–2358 (2005)

    Google Scholar 

  7. Cavallo, F., Sabatini, A.M., Genovese, V.: A step toward GPS/INS personal navigation systems: real-time assessment of gait by foot inertial sensing. In: Intelligent Robots and Systems (IROS) 2005, pp. 1187–1191 (2005)

    Google Scholar 

  8. Strömbäck, P., Rantakokko, J., Wirkander, S.-L., Alexandersson, M., Fors, I., Skog, I., Händel, P.: Foot-mounted inertial navigation and cooperative sensor fusion for indoor positioning. In: Proc. ION 2010 (2010)

    Google Scholar 

  9. Rui, G., Chitre, M.: Cooperative positioning using range-only measurements between two AUVs. In: Proc. OCEANS 2010. IEEE (2010)

    Google Scholar 

  10. Forno, F., Malnati, G., Portelli, G.: Design and Implementation of a Bluetooth ad hoc Network for Indoor Positioning. IEEE Proceedings-Softw. 152, 223–228 (2005)

    Article  Google Scholar 

  11. Welch, G., Bishop, G.: An Introduction to the Kalman Filter. Dept. Comput. Sci., Univ. North Carolina, Chapel Hill, Tech. Rep. TR95041 (2000)

    Google Scholar 

  12. Kotanen, A., Hannikainen, M., Leppakoski, H., Hamalainen, T.D.: Experiments on Local Positioning with Bluetooth. In: Proc. ITCC 2003, April 28-30, pp. 297–303 (2003)

    Google Scholar 

  13. Sheng, Z., Pollard, J.K.: Position Measurement using Bluetooth. IEEE Trans. on Consumer Electronics 52(2), 555–558 (2006)

    Article  Google Scholar 

  14. Cui, Y., Chipchase, J., Ichikawa, F.: A Cross Culture Study on Phone Carrying and Physical Personalization. In: Aykin, N. (ed.) HCII 2007. LNCS, vol. 4559, pp. 483–492. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  15. Bardwell, J.: Converting Signal Strength Percentage to dBm Values. WildPackets White Paper (2002)

    Google Scholar 

  16. Steinhoff, U., Schiele, B.: Dead Reckoning from the Pocket - An Experimental Study. In: Proc. PerCom 2010 (2010)

    Google Scholar 

  17. Kamisaka, D., Muramatsu, S., Iwamoto, T., Yokoyama, H.: Design and Implementation of Pedestrian Dead Reckoning System on a Mobile Phone. IEICE Trans. ISS E94-D(6) (2011)

    Google Scholar 

  18. Randell, C., Djiallis, C., Muller, H.: Personal Position Measurement Using Dead Reckoning. In: Proc. ISWC 2003, pp. 166–173. IEEE Computer Society (2003)

    Google Scholar 

  19. Perry, J.: Gait Analysis: Normal and Pathological Function. SLACK Incorporated, Thorofare (1992)

    Google Scholar 

  20. Weinberg, H.: Using the ADXL202 in Pedometer and Personal Navigation Applications. APPLICATION NOTE AN-602, Analog Devices, Inc. (2002)

    Google Scholar 

  21. Ministry of the Environment Government of Japan: Shinjuku Gyoen National Garden, http://www.env.go.jp/garden/shinjukugyoen/english/index.html

  22. Tokyo Metropolitan Park Association: Yoyogi Park, http://www.tokyo-park.or.jp/english/park/detail_03.html#yoyogi

  23. SOLAR PHONE SH007, http://www.sharp.co.jp/products/sh007/

  24. Harrison, C., Hudson, S.: Lightweight Material Detection for Placement-Aware Mobile Computing. In: Proc. UIST 2008, pp. 279–282 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kamisaka, D., Watanabe, T., Muramatsu, S., Kobayashi, A., Yokoyama, H. (2012). Estimating Position Relation between Two Pedestrians Using Mobile Phones. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds) Pervasive Computing. Pervasive 2012. Lecture Notes in Computer Science, vol 7319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31205-2_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31205-2_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31204-5

  • Online ISBN: 978-3-642-31205-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics