Tight integration of digital map and in-vehicle positioning unit for car navigation in urban areas
Now GPS has been widely used for land, sea and air navigation. However, due to signal blockage and severe multipath environments in urban areas, such as in Hong Kong, GPS alone can not satisfy most land vehicle navigation requirements. Dead Reckoning (DR) systems have been widely used to bridge the gaps of GPS and to smooth GPS position errors. However, the DR drift errors increase with time rapidly and frequent calibration is required. Under the normal situation, GPS is sufficient to provide the calibration to the DR unit. However, GPS may not be available in urban areas for more than 20 min, and the DR position errors can reach hundreds of meters during the period. As land vehicles have to be on roads, digital map can be used to constrain the locations of vehicles, known as map-matching. One of the main problems for map-matching techniques is mis-matching, that may be caused by the positioning sensor errors and the complexity of city road network. In this paper, a newly developed model to tightly integrate digital map and in-vehicle positioning unit for car navigation is introduced. With this method, it improves the position accuracy by constraining the vehicle location on the roads. Moreover it provides the close-loop controls for the DR drift errors by feeding back the coordinates of the feature points of the road network and road bearings to the DR unit and therefore the navigation system can be used for longer period when GPS is not available. Extensive tests have been carried out in Hong Kong. It demonstrates that this close-loop approach is much better on the reliability of map-matching, as the positioning sensor errors are constantly calibrated by the digital map.
Key wordsvehicle navigation map matching positioning GPS DR
CLC numberP 228.4 TN 967.2
Unable to display preview. Download preview PDF.
- Farrell J A, Barth M.The Global Positioning System and Inertial Navigation. New York: McGraw-Hill, 1999.Google Scholar
- Parkinson B, Axelrad P.Global Positioning System: Theory and Applications, Vol. II. Washington D C: American Institute of Aeronautics and Astronautics, 1996.Google Scholar
- Chao, C H, Chen Y Q, Chen W,et al. An Experimental Investigation into the Performance of GPS-Based Vehicle Positioning in Very Dense Urban Areas.Journal of Geospatial Engineering, 2001,3(l):59–66.Google Scholar
- Satirapod C, Razos C, Wang J. GPS Single Point Positioning with SA off: How Accuracy Can We Get?Survey Review, 2001,36(sn282):255–262.Google Scholar
- Scott C A.Improved Positioning of Motor Vehicles Through Secondary Information Sources, for the [Ph. D Thesis] Philosophy of the University of Technology, Sydney, Sep. 1996.Google Scholar
- Ad Bastiaansen MBA. The Navigable Digital Street Map Is the Critical Success Factor for Vehicle Navigation and Transport Information Systems in Europe.Intelligent Vehicles Symposium, Proceedings of the 1996IEEE, Tokyo, 1996. 117–119.Google Scholar
- Zhao Yi-lin.Vehicle Location and Navigation Systems. Boston. London: Artech House, 1997.Google Scholar
- French R L, Map Matching Origins, Approaches and Applications.Proc Second International Symposium on Land vehicle Navigation, Minister, Verlag TUV Rheinland, July 1989. 91.Google Scholar
- Bernstein D, Kornhause A. An Introduction to Map Matching for Personal Navigation Assistants, http: //www. njtide. org/reports/mapmatchintro. pdf Princeton University, August 1996.Google Scholar
- Krakiwsky E J, Harris C B, Wong R V C. A Kalman Filter for Integrating Dead Reckoning, Map Matching and GPS Positioning.Position Location and Navigation Symposium, 1988.Record. Navigation into the 21st Century. IEEE PLANS ’88,IEEE, 1988, 39–46.Google Scholar
- Takashi J, Miki H, Kitajima H. A Map Matching Method with the Innovation of the Kalman Filtering.IEICE Trans. Fundamentals, 1996,E79-A(11): 1853–1855.Google Scholar