Abstract
Vehicular positioning with multi-sensor fusion has achieved promising results in recent years. Having potential benefit from the emerging vehicular communications based on IEEE 802.11p dedicated short-range communication (DSRC), cooperative positioning opens new opportunities to support several vehicular applications. In addition, radar based active safety functions and GPS are being integrated into modern vehicles. With the availability of information from multiple sources, exchange of sensor information and multi-sensor fusion can be applied to obtain the precise positioning of vehicle without substantial additional cost. However, the main challenge in data fusion is the inherent data association problem due to dissimilar measurement update rate of DSRC and automotive radar. To overcome these challenges, this paper proposes a robust positioning approach considering track-to-track matching and fusion of position information obtained from multiple on-board sources such as GPS receiver, Vehicle-to-vehicle communication and automotive radar. Realistic 3D road traffic and wave propagation model is developed using a ray-tracing tool and the effectiveness of the proposed concept was evaluated. The system concept is validated by conducting extensive simulation considering realistic car following model. Results show that the proposed cooperative positioning method exhibits significant improvement in terms of positioning accuracy.
Similar content being viewed by others
References
Khattab, A., Fahmy, Y. A., & Wahab, A. A. (2015). High accuracy GPS-free vehicle localization framework via an INS-assisted single RSU, International Journal of Distributed Sensor Networks, 11, 795036.
Hasch, J., Topak, E., Schnabel, R., Zwick, T., Weigel, R., & Waldschmidt, C. (2012). Millimeter-wave technology for automotive radar sensors in the 77 GHz frequency band. IEEE Transactions on Microwave Theory and Techniques, 60, 845–860.
Ohguchi, K., Shono, M., & Kishida, M. (2013). 79 GHz Band Ultra-Wideband Automotive Radar. In Fujitsu Ten Tech, Journal. no. 39.
Wu, X., Subramanian, S., Guha, R., White, R. G., Li, J., Lu, K. W., et al. (2013). Vehicular communications using DSRC: Challenges, enhancements, and evolution. IEEE Journal on Selected Areas in Communications, 31, 399–408.
Rohani, M., Gingras, D., Vigneron, V., & Gruyer, D. (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, 85–95.
de Ponte Müller, F., Diaz, E. M. & Rashdan I. (2016). Cooperative positioning and radar sensor fusion for relative localization of vehicles. In IEEE Intelligent Vehicles Symposium (IV), (pp. 1060–1065).
de Ponte Müller, F. (2017). Survey on ranging sensors and cooperative techniques for relative positioning of vehicles. Sensors, 17, 271.
Fujii, S., Fujita, A., Umedu, T., Kaneda, S., Yamaguchi, H., Higashino, T., & Takai, M. (2011) Cooperative vehicle positioning via V2V communications and onboard sensors. In IEEE Vehicular Technology Conference (VTC Fall), (pp. 1–5).
Wang, J., Gao, Y., Li, Z., Meng, X., & Hancock, C. M. (2016). A tightly-coupled GPS/INS/UWB cooperative positioning sensors system supported by V2I communication. Sensors, 16, 944.
Wang, D., O’Keefe, K., & Petovello, M. G. (2013). Decentralized cooperative navigation for vehicle-to-vehicle (V2V) applications using GPS integrated with UWB range. In Proceedings of the ION Pacific PNT Conference, Honolulu, HI, USA, (pp. 22–25).
Norrdine, A (2012) An algebraic solution to the multilateration problem. In Proceedings of the 15th international conference on indoor positioning and indoor navigation, Sydney, Australia.
Remcom. Wireless Insite. Available: http://www.remcom.com/wireless-insite
Shin, Y., Seo, G., Woo, S., Ko, K., & Mun, C. (2015) Implementation of IEEE 802.11 p transceiver using USRP-RIO By LabVIEW Communications. In Vehicular networking conference (VNC), 2015 IEEE, 2015, pp. 171–172.
Kenney, J. B. (2011). Dedicated short-range communications (DSRC) standards in the United States. Proceedings of the IEEE, 99, 1162–1182.
Rohling, H., & Moller, C. (2008) Radar waveform for automotive radar systems and applications. In IEEE radar conference, pp. 1–4.
Li, L., Chen, X. M., & Zhang, L. (2016). A global optimization algorithm for trajectory data based car-following model calibration. Transportation Research Part C: Emerging Technologies, 68, 311–332.
Alexiadis, V., Colyar, J., Halkias, J., Hranac, R., & McHale, G. (2004). The next generation simulation program. Institute of Transportation Engineers. ITE Journal, 74, 22.
Hofmann-Wellenhof, B., Lichtenegger, H., & Collins, J. (2012). Global positioning system: Theory and practice. Berlin: Springer.
Viriyasitavat, W., Boban, M., Tsai, H.-M., & Vasilakos, A. (2015). Vehicular communications: Survey and challenges of channel and propagation models. IEEE Vehicular Technology Magazine, 10, 55–66.
Abbas, T. (2014). Measurement based channel characterization and modeling for vehicle-to-vehicle communications: Department of Electrical and Information Technology, Lund University, 2014.
Fernandez, H., Rubio, L., Rodrigo-Penarrocha, V. M., & Reig, J. (2014). Path loss characterization for vehicular communications at 700 MHz and 5.9 GHz under LOS and NLOS conditions. IEEE Antennas and Wireless Propagation Letters, 13, 931–934.
Taylor, G., Brunsdon, C., Li, J., Olden, A., Steup, D., & Winter, M. (2006). GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration. Computers, Environment and Urban Systems, 30, 757–772.
Mihaita, A. S., Tyler, P., Menon, A., Wen, T., Ou, Y., Chen, C., & Chen, F. (2017) An investigation of positioning accuracy transmitted by connected heavy vehicles using DSRC. In Proceedings of 96th annual meeting transportation research board, Washington DC, 2017.
Hollinger, J., Kutscher, B., & Close, R. (2015). Fusion of lidar and radar for detection of partially obscured objects. In SPIE Defense + security, pp. 946–949.
Takasu, T. & Yasuda, A. (2009) Development of the low-cost RTK-GPS receiver with an open source program package RTKLIB. In International Symposium on GPS/GNSS, pp. 4–6.
Ansari, K., Wang, C., Wang, L., & Feng, Y., (2013). Vehicle-to-vehicle real-time relative positioning using 5.9 GHz DSRC media. In IEEE vehicular technology conference (VTC), pp. 1–7.
Lin, J.-J., Li, Y.-P., Hsu, W.-C., & Lee, T.-S. (2016). Design of an FMCW radar baseband signal processing system for automotive application. SpringerPlus, 5, 42.
Houenou, A., Bonnifait, P., Cherfaoui, V., & Boissou, J.-F., (2012). A track-to-track association method for automotive perception systems. In IEEE Intelligent Vehicles Symposium, pp. 704–710.
Preacher, K. J. (2001). Calculation for the Chi square test: An interactive calculation tool for Chi square tests of goodness of fit and independence [Computer software],” ed, 2001.
Fujii, K. (2013) Extended kalman filter. Refernce Manual.
Shladover, S. E., & Tan, S.-K. (2006). Analysis of vehicle positioning accuracy requirements for communication-based cooperative collision warning. Journal of Intelligent Transportation Systems, 10, 131–140.
Acknowledgements
This research is funded through support from the University Research Program of King Abdulaziz City for Science & Technology (KACST) and Lockheed Martin Corporation (LM).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hossain, M.A., Elshafiey, I. & Al-Sanie, A. Cooperative vehicle positioning with multi-sensor data fusion and vehicular communications. Wireless Netw 25, 1403–1413 (2019). https://doi.org/10.1007/s11276-018-1772-6
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-018-1772-6