Co-operative vehicle localization algorithm - Evaluation of the CoVeL approach

International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings

Volumn , Issue , 2012, Pages

  Mattern, Norman ^a   Obst, Marcus ^a   Schubert, Robin ^a   Wanielik, Gerd ^a  

^a CHEMNITZ UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COOPERATIVE LOCALIZATION; COST-EFFICIENT; DIGITAL MAP; EUROPEAN PROJECT; GPS/INS; GROUND TRUTH DATA; HIGH AVAILABILITY; HIGH-ACCURACY; LOCALIZATION PROBLEMS; MAP MATCHING; POSITIONING ACCURACY; PUBLIC ROADS; REAL WORLD DATA; REFERENCE SYSTEMS; RELATIVE POSITIONS; ROAD NETWORK; SIMULATED DATA; URBAN ENVIRONMENTS; VEHICLE LOCALIZATION; VEHICLE-TO-VEHICLE COMMUNICATION;

ALGORITHMS; FLEET OPERATIONS; VEHICLE TO VEHICLE COMMUNICATIONS; VEHICLES;

TRACKING (POSITION);

EID: 84861626200     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SSD.2012.6198084     Document Type: Conference Paper

References (8)

1. COVEL, "Cooperative Vehicle Localization for Efficient Urban Mobility," 2010, www.covel-project.eu.
2. N. Mattern, M. Obst, R. Schubert, and G.Wanielik, "Simulative analysis of accuracy demands of co-operative localization in the covel project," in Intelligent Vehicles Symposium (IV), 2011 IEEE, june 2011, pp. 516-521.
3. M. Obst, N. Mattern, R. Schubert, and G. Wanielik, "Car-to-Car Communication for Accurate Vehicle Localization - the CoVeL Approach," in Submitted to the International Multi-Conference on Systems, Signals & Devices, Conference on Communication & Signal Processing, Accepted for publication, 2012.
4. R. Parker and S. Valaee, "Cooperative vehicle position estimation," in Communications, 2007. ICC '07. IEEE International Conference on, june 2007, pp. 5837-5842.
5. A. Edelmayer, M. Miranda, and V. Nebehaj, "Cooperative federated filtering approach for enhanced position estimation and sensor fault tolerance in ad-hoc vehicle networks," Intelligent Transport Systems, IET, vol. 4, no. 1, pp. 82-92, march 2010.
6. B. Ristic, S. Arulampalam, and N. Gordon, Beyond the Kalman Filter - Particle Filters for Tracking Applications. Artech House, 2004.
7. S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics. The MIT Press, 2005.
8. R. van der Merwe, "Sigma-Point Kalman Filters for Probabilistic Inference in Dynamic State-Space Models," Ph.D. dissertation, OGI School of Science & Engineering, Oregon Health & Science University, 2004. [Online]. Available: http://www.cse.ogi.edu/~rudmerwe/pubs/pdf/rvdmerwe-phd- thesis.pdf