Abstract
This paper presents a global positioning system for an autonomous electric vehicle based on a Real-Time Kinematic Global Navigation Satellite System (RTK- GNSS), and an incremental-encoder odometry system. Both elements are fused to a single system by an Extended Kalman Filter (EKF), reaching centimeter accuracy. Some varied experiments have been carried out in a real urban environment to compare the performance of this positioning architectures separately and fused together. The achieved aim was to provide autonomous vehicles with centimeter precision on geolocalization to navigate through a real lane net.
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References
Greaves, S., Somers, A.: Insights on driver behaviour: what can global positioning system (GPS) data tell us? Publication of ARRB Transport Research, Limited (2003)
Ren, H., Xu, T., Li, X.: Driving behavior analysis based on trajectory data collected with vehicle-mounted GPS receivers. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, vol. 39, no. 6, pp. 739–744 (2014)
Wong, I.Y.: Using GPS and accelerometry to assess older adults’ driving behaviours and performance: challenges and future directions (2013)
Sun, Q.C., Odolinski, R., Xia, J.C., Foster, J., Falkmer, T., Lee, H.: Validating the efficacy of GPS tracking vehicle movement for driving behaviour assessment. Travel. Behav. Soc. 6, 32–43 (2017)
Gao, Y., Li, Z., McLellan, J.: Carrier phase based regional area differential GPS for decimeter-level positioning and navigation. In: Proceedings of the 10th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1997), pp. 1305–1313 (1997)
Ragheb, A.E., Ragab, A.F.: Enhancement of GPS single point positioning accuracy using referenced network stations. World Appl. Sci. J. 18(10), 1463–1474 (2012)
Thitipatanapong, R., Wuttimanop, P., Chantranuwathana, S., Klongnaivai, S., Boonporm, P., Noomwongs, N.: Vehicle safety monitoring system with next generation satellite navigation: Part 1 lateral acceleration estimation. Technical report, SAE Technical Paper (2015)
Alkan, R.M., İlçi, V., Ozulu, I.M., Saka, M.H.: A comparative study for accuracy assessment of PPP technique USING GPS and GLONASS in urban areas. Measurement 69, 1–8 (2015)
Angrisano, A., Gaglione, S., Gioia, C.: Performance assessment of GPS/GLONASS single point positioning in an urban environment. Acta Geodaetica et Geophysica 48(2), 149–161 (2013)
Verhagen, S., Odijk, D., Teunissen, P.J., Huisman, L.: Performance improvement with low-cost multi-GNSS receivers. In: 2010 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), pp. 1–8. IEEE (2010)
Odolinski, R., Teunissen, P.J., Odijk, D.: Combined BDS, galileo, QZSS and GPS single-frequency RTK. GPS Solut. 19(1), 151–163 (2015)
Naranjo, J.E., González, C., García, R., De Pedro, T., Haber, R.E.: Power-steering control architecture for automatic driving. IEEE Trans. Intell. Transp. Syst. 6(4), 406–415 (2005)
Rezaei, S., Sengupta, R.: Kalman filter-based integration of DGPS and vehicle sensors for localization. IEEE Trans. Control. Syst. Technol. 15(6), 1080–1088 (2007)
Weinstein, A.J., Moore, K.L.: Pose estimation of Ackerman steering vehicles for outdoors autonomous navigation. In: 2010 IEEE International Conference on Industrial Technology (ICIT), pp. 579–584. IEEE (2010)
LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)
Welch, G., Bishop, G.: An introduction to the Kalman filter. University of North Carolina, Department of Computer Science. Technical report, TR 95-041 (1995)
Acknowledgment
This work has been partially funded by the Spanish MINECO/FEDER through the SmartElderlyCar project (TRA2015-70501-C2-1-R), the DGT through the SERMON project (SPIP2017-02305), and from the RoboCity2030-III-CM project (Robótica aplicada a la mejora de la calidad de vida de los ciudadanos, fase III; S2013/MIT-2748), funded by Programas de actividades I+D (CAM) and cofunded by EU Structural Funds.
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Tradacete, M. et al. (2019). Positioning System for an Electric Autonomous Vehicle Based on the Fusion of Multi-GNSS RTK and Odometry by Using an Extented Kalman Filter. In: Fuentetaja Pizán, R., García Olaya, Á., Sesmero Lorente, M., Iglesias Martínez, J., Ledezma Espino, A. (eds) Advances in Physical Agents. WAF 2018. Advances in Intelligent Systems and Computing, vol 855. Springer, Cham. https://doi.org/10.1007/978-3-319-99885-5_2
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DOI: https://doi.org/10.1007/978-3-319-99885-5_2
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