Acquisition of Relative Trajectories of Surrounding Vehicles using GPS and SRC based V2V Communication with Lane Level Resolution

Zhiyuan Peng, Shah Hussain, M. I. Hayee, Max Donath

Abstract

Due to the anticipated benefits of connected vehicle technology, the Intelligent Transportation Systems Joint Program Office (ITSJPO) of the US Department of Transportation continues to emphasize the need for dedicated short range communication (DSRC) based vehicle-to-vehicle (V2V) and/or vehicle-to-infrastructure (V2I) communication to enhance driver safety and traffic mobility. To take full advantage of connected vehicle technology in most safety applications, precise vehicle positioning information is needed in addition to V2V communication. Many techniques, such as vision- or sensor-based systems and differential GPS receivers, can obtain the precise absolute position of a vehicle at the expense of cost and complexity. However, some critical safety applications such as merge-assist or lane-change-assist systems require only the relative positions of surrounding vehicles with lane-level resolution so that a given vehicle can differentiate the vehicles in its own lane from the vehicles in adjacent lanes. We have adopted a simple approach to acquire accurate relative trajectories of surrounding vehicles using standard GPS receivers and DSRC-based V2V communication. Using this approach, we have conducted field tests to successfully acquire relative trajectories of vehicles traveling in multiple lanes towards a merging junction with an accuracy less than half of the lane width. The achieved accuracy level of the relative trajectory was sufficient to differentiate vehicles traveling in adjacent lanes of a multiple-lane freeway.

References

  1. Intelligent Transportation Systems - DSRC: The Future of Safer Driving Fact Sheet. 2017. Intelligent Transportation Systems - DSRC: The Future of Safer Driving Fact Sheet. [ONLINE] Available at: http://www.its.dot.gov/factsheets/dsrc_factsheet.htm. [Accessed 23 February 2017].
  2. Intelligent Transportation Systems. 2017. Connected Vehicle Challenges: Potential Impact of Sharing the 5.9 GHZ Wireless Spectrum. [ONLINE] Available at: Http://www.its.dot.gov/cv_basics/pdf/CV_basics_DS RC_factsheet.pdf. [Accessed 23 February 2017].
  3. Harding, J., Powell, G., R., Yoon, R., Fikentscher, J., Doyle, C., Sade, D., Lukuc, M., Simons, J., & Wang, J. (2014, August). Vehicle-to-vehicle communications: Readiness of V2V technology for application. (Report No. DOT HS 812 014). Washington, DC: National Highway Traffic Safety Administration.
  4. U.S. Department of Transportation. 2017. Vehicle to Vehicle Communication Fact Sheet National Highway Traffic Safety Administration, US Department of Transportation. [ONLINE] Available at: Http://www.nhtsa.gov/pdf/v2v_fact_sheet02032014.pdf. [Accessed 23 February 2017].
  5. D. Jie and M. J. Barth, 2008. Next-generation automated vehicle location systems: Positioning at the lane level, IEEE Trans. Intell. Transp. Syst., vol. 9, no. 1, pp. 48- 57, 2008.
  6. S. Ammoun, F. Nashashibi and C. Laurgeau, 2007, An analysis of the lane changing manoeuvre on roads: The contribution of inter-vehicle cooperation via communication, IEEE Intelligent Vehicles Symposium pp. 1095-1100, June 2007.
  7. D. Desiraju, T. Chantem. K. Heaslip, 2015. Minimizing the Disruption of Traffic Flow of Automated Vehicles During Lane Changes", Intelligent Transportation Systems, IEEE Transactions, pp. 1249 - 1258 Volume: 16, Issue: 3, June 2015.
  8. A.T. McCartt et al., 2004. Types and characteristics of ramp-related motor vehicle crashes on urban interstate roadways in Northern Virginia”, Journal of Safety Research, vol.35, 2004, pp. 107- 114.
  9. Bruce N. Janson, Wael Awad, Juan Robles, Jake Kononov, Brian Pinkerton, 1998. Truck Accidents at Freeway Ramps: Data Analysis and High-Risk Site Identification, Journal of Transportation and Statistics, January 1998, pp. 75 - 92.
  10. Basav Sen, John D. Smith, and Wassim G. Najm. 2003. Analysis of Lane Change Crashes. DOT-VNTSCNHTSA-02-03 DOT HS 809 571, March 2003.
  11. G. M. Fitch, S. E. Lee, S. Klauer, J. Hankey, J. Sudweeks, and T. Dingus, 2009. Analysis of Lane-Change Crashes and Near-Crashes DOT HS 811 147, June 2009.
  12. National Highway Traffic Safety Administration. 2008. National Motor Vehicle Crash Causation Survey: Report to Congress. DOT HS 811 059, July 2008.
  13. D Chun; K, Stol., 2012. Vehicle motion estimation using low-cost optical flow and sensor fusion, Mechatronics and Machine Vision in Practice (M2VIP), 2012 19th International Conference, pp. 507 - 512, Nov. 2012.
  14. Abdelfatah, W.F., et al., 2011. "2D Mobile multi-sensor navigation system realization using FPGA-based embedded processors," Canadian Conference on Electrical and Computer Engineering (CCECE), 2011, pp. 1218-1221.
  15. Qingquan Li et al., 2014. A Sensor-Fusion DrivableRegion and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios, Vehicular Technology, IEEE Transactions on, Volume: 63, Issue: 2, pp. 540 - 555, Feb. 2014.
  16. H. Zhao, M. Chiba, R. Shibasaki, X. Shao, J. Cui and H. Zha, 2009. A laser-scanner-based approach toward driving safety and traffic data collection, IEEE Trans. Intell. Transp. Syst., vol. 10, no. 3, pp. 534-546, 2009.
  17. A. Bansal, H. Badino and D. Huber, 2014. Understanding how camera configuration and environmental conditions affect appearance-based localization, Intelligent Vehicles Symposium Proceedings (IV), 2014 IEEE, pp. 800-807.
  18. R. Toledo-Moreo, M. A. Zamora-Izquierdo, B. UbedaMinarro, and A. F. Gomez-Skarmeta, 2007. Highintegrity IMM-EKF-based road vehicle navigation with low-cost GPS/SBAS/INS, IEEE Transaction on Intelligent Transportation Systems., vol. 8, no. 3, pp. 491-511, Sep. 2007.
  19. N. Mattern, R. Schubert, and G. Wanielik, 2010. Highaccurate vehicle localization using digital maps and coherency images, in Proc. IEEE Intell. Vehicles Symposium, La Jolla, CA, 2010, pp. 462-469.
  20. R. G. García-García, M. A. Sotelo, I. Parra, D. Fernández, and M. Gavilán, 2007. 3D visual odometry for GPS navigation assistance, in Proc. IEEE Intell. Vehicles Symposium, Istanbul, Turkey, 2007, pp. 444-449.
  21. J. Juang; C. Lin., 2015. A Sensor Fusion Scheme for the Estimation of Vehicular Speed and Heading Angle, Vehicular Technology, IEEE Transactions on, pp. 2773 - 2782 Volume: 64, Issue: 7, July 2015.
  22. S. Rezaei and R. Sengupta, 2007. “Kalman filter-based integration of DGPS and vehicle sensors for localization,” IEEE Trans. Control Syst. Technol., vol. 15, no. 6, pp. 1080-1088, Nov. 2007.
  23. N. Alam, A. T. Balaei and A. G. Dempster, 2013. Relative positioning enhancement in VANETs: A tight integration approach", IEEE Trans. Intell. Transp. Syst., vol. 14, no. 1, pp. 47-55, 2013.
  24. J. Farrell, T. Givargis, 2000. Differential GPS Reference Station Algorithm-design and Analysis. In IEEE Transactions on Control Systems Technology, Vol. 8, No. 3, May 2000, pp. 519-531.
  25. High Accuracy-Nationwide Differential Global Positioning System Program Fact Sheet - FHWA-RD03-039. 2017. High Accuracy-Nationwide Differential Global Positioning System Program Fact Sheet - FHWA-RD-03-039. [ONLINE] Available at: https://www.fhwa.dot.gov/publications/research/operat ions/03039/. [Accessed 23 February 2017].
  26. William J. Hughes. July 2014. Federal Aviation Administration, Global Positioning System (GPS) Standard Positioning Service (SPS) Performance Analysis Report #86 Technical Centre NSTB/WAAS T&E Team.
  27. D. K. Schrader, 2013. Combining Multiple, Inexpensive GPS Receivers to Improve Accuracy and Reliability", Sensors Applications Symposium (SAS), 2013 IEEE. pp. 33-37.
  28. R. B. Langley, 1997. GPS receiver system noise, GPS World, vol. 8, no. 6, pp. 40-45, 1997.
  29. Ahmed El-Rabbany, 2002. Introduction to GPS: The Global Positioning System. 2002, pp.29.
  30. T. Kos, I. Markezic and J. Pokrajcic, 2010. Effects of multipath reception on GPS positioning performance, ELMAR, 52nd International Symposium EL MAR2010, pp. 399-402.
  31. D.Jiang, V.Taliwal, A.Meier and W. Holfelder, 2006. Design of 5.9 GHz DSRC-based Vehicular Safety Communication, IEEE Wireless Communications, Vol. 13, No 5, October 2006, pp.36-43.
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Paper Citation


in Harvard Style

Peng Z., Hussain S., Hayee M. and Donath M. (2017). Acquisition of Relative Trajectories of Surrounding Vehicles using GPS and SRC based V2V Communication with Lane Level Resolution . In Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-242-4, pages 242-251. DOI: 10.5220/0006304202420251


in Bibtex Style

@conference{vehits17,
author={Zhiyuan Peng and Shah Hussain and M. I. Hayee and Max Donath},
title={Acquisition of Relative Trajectories of Surrounding Vehicles using GPS and SRC based V2V Communication with Lane Level Resolution},
booktitle={Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2017},
pages={242-251},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006304202420251},
isbn={978-989-758-242-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Acquisition of Relative Trajectories of Surrounding Vehicles using GPS and SRC based V2V Communication with Lane Level Resolution
SN - 978-989-758-242-4
AU - Peng Z.
AU - Hussain S.
AU - Hayee M.
AU - Donath M.
PY - 2017
SP - 242
EP - 251
DO - 10.5220/0006304202420251