Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-18T21:18:52.893Z Has data issue: false hasContentIssue false

Can Low-Cost Road Vehicles Positioning Systems Fulfil Accuracy Specifications of New ADAS Applications?

Published online by Cambridge University Press:  02 March 2011

F. Jiménez*
Affiliation:
(Universidad Politécnica de Madrid)
J. E. Naranjo
Affiliation:
(Universidad Politécnica de Madrid)
F. García
Affiliation:
(Universidad Carlos III de Madrid)
J. M. Armingol
Affiliation:
(Universidad Carlos III de Madrid)
*

Abstract

Some new Advanced Driver Assistance Systems (ADAS) need on-the-lane vehicle positioning on accurate digital maps, but current applications of vehicle positioning do not justify the surcharge of very accurate equipment such as DGPS or high-cost inertial systems. For this reason, the performance of GPS in autonomous mode is analyzed. Although satisfactory results can be found, in some areas the GPS signal is lost or degraded so it is necessary to know the positioning error when using only inertial system data. A theoretical approach based on the uncertainty propagation law is used to estimate the upper limit of distance that can be travelled fulfilling the specifications of an assistance system. Test results support the conclusions of this approach. Finally, the combination of GPS and inertial systems is studied, with the conclusion that the theoretical approach is valid when inertial measurements are used right from the start of GPS signal degradation, without waiting for a complete loss of signal.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Alexander, L., Cheng, P. M., Donath, M., Gorjestani, A., Newstrom, B., Shankwitz, C., Trach, W. (2005). Bus rapid transit Technologies: assisting drivers operating buses on road shoulders. University of Minnesota.Google Scholar
Alkan, R. M., Saka, M. H. (2009). A performance analysis of low-cost GPS receivers in kinematic applications. The Journal of Navigation, 62 (4), 687697CrossRefGoogle Scholar
Baselga, S., García-Asenjo, L., Garrigues, P., Lerma, J. L. (2009). Inertial navigation system data filtering prior to GPS/INS integration. The Journal of Navigation, 62, 711720CrossRefGoogle Scholar
Baum, G. (2003). The infrastructure and evolution of mapmaking. Proceedings of the 10th World Congress and Exhibition on Intelligent Transport Systems and Services. Madrid: 16–20 November 2003Google Scholar
Ben-Arieh, D., Chang, S., Rys, M., Zhang, G. (2004). Geometric modelling of highways using global positioning system data and B-spline approximation. Journal of Transportation Engineering, 130(5), 632636Google Scholar
Bendafi, H., Hummelsheim, K., Sabel, H., van de Ven, S. (2000). Classification of data capturing / production techniques. NextMap Project Deliverable D 3.1.Google Scholar
Borenstein, J., Ojeda, L., Kwanmuang, S. (2009). Heuristic reduction of gyro drift for personnel tracking systems. The Journal of Navigation, 62, 4158CrossRefGoogle Scholar
Castro, M., Iglesias, L., Rodríguez-Solano, R., Sánchez, J. A. (2006). Geometric modelling of highways using global positioning system (GPS) data and spline approximation. Transportation Research. Part C: Emerging Technologies, 14(4), 233243CrossRefGoogle Scholar
Drakopoulos, A., Örnek, E. (2000). Use of vehicle-collected data to calculate existing roadway geometry. Journal of transportation engineering, 126(2), 154160CrossRefGoogle Scholar
EDMap Consortium. (2004). Enhanced digital mapping project. Final report. EDMap Project eSafety Forum. (2005). Digital maps Working Group Final Report. European Commission (eSafety Forum), Brussels.Google Scholar
European co-operation for Accreditation. (1999). Expression of uncertainty of measurement in calibration. Publication reference EA-4/02.Google Scholar
Han, S., Wang, J. (2010). Land Vehicle Navigation with the Integration of GPS and Reduced INS: Performance Improvement with Velocity Aiding. The Journal of Navigation, 63, 153166CrossRefGoogle Scholar
Imran, M., Hassan, Y., Patterson, D. (2006). GPS-GIS based procedure for tacking vehicle path on horizontal alignments'. Computer – Aided Civil and Infrastructure Engineering, 21(5), 383394CrossRefGoogle Scholar
Jiménez, F., Aparicio, F., Páez, J. (2008). Evaluation of in-vehicle dynamic speed assistance in Spain: algorithm and driver behaviour. IET Intelligent Transport Systems, 2(2), 132142CrossRefGoogle Scholar
Jiménez, F., Aparicio, F., Estrada, G. (2009). Measurement uncertainty determination and curve fitting algorithms for development of accurate digital maps for Advanced Driver Assistance Systems. Transportation Research Part C: Emerging Technologies, 17(3), 225239CrossRefGoogle Scholar
Jiménez, F., Naranjo, J. E. (2009). Nuevos requerimientos de precisión en el posicionamiento de vehículos para aplicaciones ADAS. Dyna Ingeniería e Industria, 84(3), 245250 (in Spanish)Google Scholar
Jwo, D. H., Huang, H. C. (2004). Neural network aided adaptive extended Kalman filtering approach for DGPS positioning. Journal of Navigation, 57, 449463.CrossRefGoogle Scholar
Jwo, D.-J., Lai, S.-Y. (2009). Navigation integration using the fuzzy strong tracking unscented Kalman Filter. The Journal of Navigation, 62, 303322CrossRefGoogle Scholar
Kwon, E., Kim, S., Betts, R. (2003). Route-based dynamic pre-emption of traffic signals for emergency vehicle operations. National research Council. Transportation research Board.Google Scholar
Labrech, A., Boucher, C., Noyer, J. C. (2004). Fusion of GPS and odometer measurements for map-based vehicle navigation. Proceedings IEEE International conference on industrial technology. Tunisia, 2004.Google Scholar
Lee, J. K., Jekeli, C. (2009). Improved filter strategies for precise geolocation of Unexploded Ordnance using IMU/GPS integration. The Journal of Navigation, 62, 365382CrossRefGoogle Scholar
Lee, J. K., Jekeli, C. (2010). Neural network aided adaptive filtering and smoothing for an integrated INS/GPS Unexploded Ordnance Geolocation System. The Journal of Navigation, 63, 251267.CrossRefGoogle Scholar
Lu, M., Wevers, K., van der Heijden, R., Heijer, T. (2004). ADAS applications for improving traffic safety. Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. The Hague, The Netherlands, 10–13 October 2004Google Scholar
Miles, J. C., Chen, K. (2004). ITS Handbook. PIARCGoogle Scholar
Naranjo, J. E., Jiménez, F., Aparicio, F., Zato, J. (2009). GPS and inertial systems for high precision positioning on motorways. The Journal of Navigation, 62, 351363Google Scholar
Njord, J., Peters, J., Freitas, M., Warner, B., Allred, K. C., Bertini, R., Bryant, R., Callan, R., Knopp, M., Knowlton, L., López, C., Warne, T. (2006). Safety applications of intelligent transportation systems in Europe and Japan. Federal Highway Administration. U.S. Department of Transportation.Google Scholar
Noronha, V., Goodchild, M. F. (2000). Map accuracy and location expression in transportation – reality and prospects. Transportation Research. Part C: Emerging Technologies, 8, (1), 5369CrossRefGoogle Scholar
Organisation for Economic Co-operation and Development. (2003). Road Safety. Impacof New Technologies. OECD Publications (France)Google Scholar
Pandazis, J. C. (2006). NEXTMAP: Investigating the Future of Digital Maps Databases, NEXTMAP UE Project Paper 2183.Google Scholar
Reichart, G., Friedmann, S., Dorrer, C., Rieker, H., Drechsel, E., Wermuth, G. (1998). Potentials of BMW Driver Assistance to Improve Fuel Economy. Proceedings of the FISITA World Automotive Congress, Paris, 27 September–1 October 1998.Google Scholar
Rezaei, S., Sengupta, R. (2007). Kalman filter based integration of DGPS and vehicle sensors for localization. IEEE Transactions on Control Systems Technology, 15(6), 10801088.CrossRefGoogle Scholar
Taylor, B. N., Kuyatt, C. E. (1994). Guidelines for evaluating and expressing the uncertainty of NIST measurement results. National Institute of Standards and Technology.CrossRefGoogle Scholar
Toledo-Moreo, R., Zamora-Izquierdo, M. A., Úbeda-Miñarro, B., Gómez-Skarmeta, A. F. (2007). High-integrity IMM-EKF-based road Vehicle navigation with low-cost GPS/SBAS/INS. IEEE Transactions on Intelligent Transportation Systems, 8(3), 491511CrossRefGoogle Scholar
Transportation Research Board. (2002). Collecting, Processing and integrating GPS data into GIS. Transportation Research Board.Google Scholar
T'Siobbel, S., van Essen, R. (2004). The map enabled ADAS future. Proceedings of the FISITA World Automotive Congress, Barcelona, 23–27 May 2004.Google Scholar
T'Siobbel, S., Otto, H. U., Kopp, D., Wevers, K., Sabel, H., Hendriks, T., Löwenau, J., Neukirchner, E.-P., Herrig, K., Ress, C., Angenvoort, J., Anderson, H., Vogt, W., Varchmin, A., Pandazis, J. C., Heinig, K. (2004). Map&ADAS subproject. Safety Digital Maps requirements. Deliverable 12.31 of the Map&ADAS subproject of the PREVENT project.Google Scholar
Venhovens, P. J. T., Bernasth, J. H. Löwenau, J. P., Rieker, H. G., Schraut, M. (1999). The application of advanced vehicle navigation in BMW driver assistance systems. SAE paper n° 1999-01-0490Google Scholar
Wevers, K., Lu, M. (2007). Digital maps, driving systems and traffic safety: the data chain for in-vehicle map databases. Proceedings of the 6th European Congress and Exhibition on Intelligent Transport Systems and Services. Aalborg: 18–20 June 2007Google Scholar
Xu, H., Wang, C., Yang, M. and Yang, R. (2008). Position estimation for intelligent vehicles using an unscented Kalman filter. International Journal of Vehicle Autonomous Systems, 6(1/2), 186194.CrossRefGoogle Scholar
Xu, Z., Li, Y., Rizos, C., Xu, X. (2010). Novel hybrid of LS-SVM and Kalman filter for GPS/INS integration. The Journal of Navigation, 63, 289299Google Scholar
Yerpez, J., Ferrandez, F. (1986). Road characteristics and safety. Identification of the part played by road factors in accident generation. INRETS, 1986Google Scholar
Zhang, Y., Gao, Y. (2008). Integration of INS and un-differenced GPS measurements for precise position and attitude determination. The Journal of Navigation, 61, 8797CrossRefGoogle Scholar