[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Log in

A Target Position Decision Algorithm Based on Analysis of Path Departure for an Autonomous Path Keeping System

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

To realize a path keeping system (PKS), it is essential to guide autonomous vehicle (AV) to a desired direction while maintaining safety. To maintain a desired driving path, it is necessary for an AV to perceive its surrounding environment by gathering directional information while traveling. Therefore, precise localization of an AV and autonomous guidance are essential technologies for the successful implementation of a PKS. As a type of radio guidance, an AV can use trilateration to identify its location relative to three reference positions by measuring the strength, time, or time difference of the reception of transmitted radio signals. Direction of arrival (DOA) techniques can also be used to estimate the direction of a signal emitted from a transmitter, and this information can be used to set the driving direction of an AV. However, in a practical environment, estimation errors may arise when the AV estimates its location or the direction of signal emitted from a transmitter, and these errors may cause the problem of path departure. To address this problem, we conducted a mathematical analysis to identify potential errors in estimating location and direction. Herein we propose a target position decision algorithm for PKS, which uses trilateration and DOA (PKS-TnD) to drive an AV in a desired direction to avoid path departure. By using this algorithm, an AV calculates its next target position based on the error constraints of trilateration and DOA by means of numerical analysis. Additionally, an energy efficiency problem is also formulated herein and energy use is optimized by using a Lagrangian equation.

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

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Yang, X., Liu, J., Zhao, F., & Vaidya, N. (2004). A Vehicle-to-vehicle communication protocol for cooperative collision warning. In Proceeding IEEE international conference on MOBIQUITOUS, pp. 114–123.

  2. Biswas, S., Tatchikou, R., & Dion, F. (2006). Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety. IEEE Communications Magazine, 44(1), 74–82.

    Article  Google Scholar 

  3. Sepulcre, M., Gozalvez, J., & Hernandez, J. (2013). Cooperative vehicle-to-vehicle active safety testing under challenging conditions. Transportation Research Part C: Emerging Technologies, 26, 233–255.

    Article  Google Scholar 

  4. Zhao, J., & Cao, G. (2008). VADD: Vehicle-assisted data delivery in vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 57(3), 1910–1922.

    Article  MathSciNet  Google Scholar 

  5. Bitam, S., Mellouk, A., & Zeadally, S. (2013). HyBR: A hybrid bio-inspired bee swarm routing protocol for safety applications in vehicular ad hoc NETworks (VANETs). Journal of Systems Architecture, 59(10), 953–967.

    Article  Google Scholar 

  6. Isomoto, K., Niibe, T., Suetomi, T., & Butsuen, T. (1995). Development of a lane-keeping system for lane departure avoidance. In Steps forward. Intelligent transport systems world congress, pp. 1266–1271.

  7. Eidehall, A., Pohl, J., Gustafsson, F., & Ekmark, J. (2007). Toward autonomous collision avoidance by steering. IEEE Transactions on Intelligent Transportation Systems, 8(1), 84–94.

    Article  Google Scholar 

  8. Jung, H., Min, J., & Kim, J. (2013). An efficient lane detection algorithm for lane departure detection. In Proceeding IEEE intelligent vehicles symposium, pp. 976–981.

  9. Li, Q., et al. (2014). A sensor-fusion drivable-region and lane-detection system for autonomous vehicle navigation in challenging road scenarios. IEEE Transactions on Vehicular Technology, 63(2), 540–555.

    Article  Google Scholar 

  10. Gezici, S., et al. (2005). Localization via ultra-wideband radios. IEEE Signal Processing Magazine, 22(4), 70–84.

    Article  Google Scholar 

  11. Chitte, S. D., Dasgupta, S., & Ding, Z. (2009). Distance estimation from received signal strength under log-normal shadowing: Bias and variance. IEEE International Conference on Signal Processing (ICSP), 16(3), 216–218.

    Article  Google Scholar 

  12. Wang, Z., & Zekavat, S. A. (2009). A novel semidistributed localization via multinode TOA–DOA fusion. IEEE Transactions on Vehicular Technology, 58(7), 3426–3435.

    Article  Google Scholar 

  13. D’Amico, A. A., Mengali, U., & Taponecco, L. (2010). TOA estimation with the IEEE 802.15.4a standard. IEEE Transactions on Wireless Communications, 9(7), 2238–2247.

    Article  Google Scholar 

  14. Gillette, M. D., & Silverman, H. F. (2008). A linear closed-form algorithm for source localization from time-differences of arrival. IEEE Signal Processing Letters, 15, 1–4.

    Article  Google Scholar 

  15. Yang, L., & Ho, K. C. (2009). An approximately efficient TDOA localization algorithm in closed-form for locating multiple disjoint sources with erroneous sensor positions. IEEE Transactions on Signal Processing, 57(12), 4598–4615.

    Article  MathSciNet  Google Scholar 

  16. Godrich, H., Haimovich, A. M., & Blum, R. S. (2010). Target localization accuracy gain in MIMO radar-based systems. IEEE Transactions on Information Theory, 56(6), 2783–2803.

    Article  MathSciNet  Google Scholar 

  17. He, Q., & Blum, R. S. (2010). Cramer–Rao bound for MIMO radar target localization with phase errors. IEEE Signal Processing Letters, 17, 83–86.

    Article  Google Scholar 

  18. Thomas, F., & Ros, L. (2005). Revisiting trilateration for robot localization. IEEE Transactions on Robotics, 21(1), 93–101.

    Article  MathSciNet  Google Scholar 

  19. Tseng, Y. C., Hsu, C. S., & Hsieh, T. Y. (2003). Power-saving protocols for IEEE 802.11-based multi-hop ad hoc networks. Computer Networks, 43(1), 317–337.

    Article  Google Scholar 

  20. Ye, W., Heidemann, H., & Estrin, D. (2004). Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Transactions on Networking, 12(3), 493–506.

    Article  Google Scholar 

  21. Tse, D., & Viswanath, P. (2005). Fundamentals of wireless communication. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  22. Shukla, M., & Hegde, R. M. (2010). Significance of the MUSIC-group delay spectrum in speech acquisition from distant microphones. In Proceeding IEEE international conference on acoustics, speech, signal processing (ICASSP), pp. 2738–2741.

  23. Winkelbauer, A. (2012). Moments and absolute moments of the normal distribution, arXiv preprint. arXiv:1209.4340.

  24. Hahnel, D., et al. (2004). Mapping and localization with RFID technology. In Proceeding IEEE international conference on robotics and automation (ICRA), pp. 1015–1020.

Download references

Acknowledgments

This research was supported by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the C-ITRC (Convergence Information Technology Research Center) support program (NIPA-2014-H0401-14-1006) supervised by the NIPA (National IT Industry Promotion Agency). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2013R1A1A2A10011764).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sanghoon Lee.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kwon, B., Park, J. & Lee, S. A Target Position Decision Algorithm Based on Analysis of Path Departure for an Autonomous Path Keeping System. Wireless Pers Commun 83, 1843–1865 (2015). https://doi.org/10.1007/s11277-015-2485-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-015-2485-0

Keywords

Navigation