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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-420d16eb-dfe5-4651-8e10-cbf734bb09f2

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Archiwum Fotogrametrii, Kartografii i Teledetekcji

Tytuł artykułu

A cooperative positioning algorithm for DSRC enabled vehicular networks

Autorzy Efatmaneshnik, M.  Kealy, A.  Alam, N.  Dempster, A. 
Treść / Zawartość
Efatmaneshnik.pdf
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Many of the safety related applications that can be facilitated by Dedicated Short Range Communications (DSRC), such as vehicle proximity warnings, automated braking (e.g. at level crossings), speed advisories, pedestrian alerts etc., rely on a robust vehicle positioning capability such as that provided by a Global Navigation Satellite System (GNSS). Vehicles in remote areas, entering tunnels, high rise areas or any high multipath/ weak signal environment will challenge the integrity of GNSS position solutions, and ultimately the safety application it underpins. To address this challenge, this paper presents an innovative application of Cooperative Positioning techniques within vehicular networks. CP refers to any method of integrating measurements from different positioning systems and sensors in order to improve the overall quality (accuracy and reliability) of the final position solution. This paper investigates the potential of the DSRC infrastructure itself to provide an intervehicular ranging signal that can be used as a measurement within the CP algorithm. In this paper, time-based techniques of ranging are introduced and bandwidth requirements are investigated and presented. The robustness of the CP algorithm to inter-vehicle connection failure as well as GNSS dropouts is also demonstrated using simulation studies. Finally, the performance of the Constrained Kalman Filter used to integrate GNSS measurements with DSRC derived range estimates within a typical VANET is described and evaluated.
Słowa kluczowe
PL DSRC   Vanet   pozycjonowanie   godzina przyjazdu   CRLB   filtracja Kalmana  
EN DSRC   Vanet   cooperative positioning   ranging   time of arrival   CRLB   Kalman filtering   robust positioning  
Wydawca Zarząd Główny Stowarzyszenia Geodetów Polskich
Czasopismo Archiwum Fotogrametrii, Kartografii i Teledetekcji
Rocznik 2011
Tom Vol. 22
Strony 117--129
Opis fizyczny Bibliogr. 12 poz.
Twórcy
autor Efatmaneshnik, M.
autor Kealy, A.
autor Alam, N.
  • School of Surveying and Spatial Information Systems, University of New South Wales, 2052, Australia, nima.alam@unsw.edu.au
autor Dempster, A.
  • School of Surveying and Spatial Information Systems, University of New South Wales, 2052, Australia, a.dempster@unsw.edu.au
Bibliografia
1. Alam, N., Balaei, A. T., & Dempster, A. G., 2009, 1-3 Dec., 2009. Range and range-rate measurements using DSRC: facts and challenges. Paper presented at the IGNSS Symposium 2009, Surfers Paradise ,Australia.
2. Bernstein, D., & Kornhauser, A., 1996. An Introduction to Map Matching for Personal Navigation Assistants. Newark, New Jersey: TIDE Center.
3. Bétaille, D., & Bonnifait, P., 2000. Road Maintenance Vehicles Location using DGPS, Map-Matching and Dead-Reckoning: Experimental Results of a Smoothed EKF. Paper presented AT the IAIN World Congress in Association with the U.S. ION 56th Annual Meeting, San Diego.
4. Bonnifait, P., Bouron, P., Crubille, P., & Meizel, D., 2001. Data fusion of four ABS sensors and GPS for an enhanced localization of car-like vehicles. Paper presented at the Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on.
5. CAMP-Vehicle-Safety-Communications-Consortium. 2005. Vehicle Safety Communications Project Task 3 Final Report, Identify Intelligent Vehicle Safety Applications Enabled by DSRC: U.S. Depatment of Transporation, National Highway Traffic Safety Administration.
6. Greenfeld, J. S., 2002. Matching GPS Observations to Locations on a Digital Map. Newark: Department of Civil and Environmental Engineering, New Jersey Institute of Technology.
7. Kealy, A., Scott-Young, A., & Collier, P., 2004. Improving Land Vehicle Safety Using Augmented Reality Technologies. Paper presented at the 4th International Symposium on Mobile Mapping Technology, Kunming, China.
8. Patwari, N., Ash, J. N., Kyperountas, S., Hero Iii, A. O., Moses, R. L., & Correal, N. S., 2005. Locating the nodes: Cooperative localization in wireless sensor networks. IEEE Signal Processing Magazine, 22, pp. 54-69.
9. Sakagami, S., Aoyama, S., Kuboi, K., Shirota, S., & Akeyama, A., 1992. Vehicle position estimates by multibeam antennas in multipathenvironments. IEEE Transactions on Vehicular Technology, 41(1), pp. 63-68.
10. Savvides, A., Garber, W., Adlakha, S., Moses, R., & Srivastava, M., 2003. On the Error Characteristics of Multihop Node Localization in Ad-Hoc Sensor Networks. In Information Processing in Sensor Networks, pp. 555-555.
11. Stephen, J. E., 2000. Development of a GNSS-based Multi-Sensor Vehicle Navigation System. University of Calgary.
12. Taylor, G., Blewitt, G., Steup, D., Corbett, S., & Car, A., 2001. Road Reduction Filtering for GPS-GIS Navigation. Transactions in GIS, 5(3), pp. 193-207.
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