The issue of Autonomous vehicle navigation has shown rapid progress due to advent of computer integration in mechanics. The field is developing due to tremendous size reduction in Electronic devices allowing us to embed the computing power into these mobile machines. The with final integration of Embedded Systems and Mechanics these vehicles will one day definitely become autonomous. Auto Cruise Control (ACC) is the technology in present implementation does this work efficiently. But ACC is just the start. Many more ways are available like, Path Tracking, Visual Target Tracking are being implemented using Fuzzy Logic and other Artificial Intelligence techniques. The sole aim is to make system Automatic. But every automatic system if given extensive degree of freedom then it tends to give unwanted or unexpected results, no matter how intelligent the system is. So aim of our idea is to confine the intelligence of these vehicles in some Protocols or Laws so that the domain of decisions by system is under control or even already known. Employing Fuzzy Logic we are making the decision structure of autonomous vehicles intelligent but also designing these in forms of protocols itself.

1. Dissanayake, P. Newman, S. Clark, H. Durrant-Whyte, and M. Csorba, " A solution to the simultaneous localization and map building (SLAM) problem. " IEEE Transactions on Robotics and Automation. Vol 17 No 3 2001, pp 229-241
2. J. Guivant, and E. Nebot, "Optimization of the simultaneous localization and map-building algorithm for real-time implementation. " IEEE Transactions on Robotics and Automation. Vol 17 No 3 2001, pp 242- 257.
3. S. Thrun, "Robotic Mapping: A Survey", Technical report, CMU-CS-02-111, School of Computer Science, Carnegie Mellon University, Pittsburg, PA 15213, Feb 2002.
4. J. –D. Tardos, J. Neira, P. -M. Newman and J. -J. Leonard, "Robust Mapping and Localization in Indoor Environments Using Sonar Data", The International journal of Robotics Research, Vol. 21, No. 4, April 2002, pp. 311-330.
5. J. -A. Perez, J. -A. Castellanos, J. -M. Montiel, J. Neira and J. -D. Tardos, "Continuous Mobile Robot Localization: Vision vs. Laser", Proc. 1999 IEEE Intl. Conf. on Robotics and Automation, Detroit, Michigan, May 1999, pp. 2917-2923.
6. M. Gavish and A. Weiss, "Performance analysis of bearing-only target location algorithms. " IEEE Transactions on Aerospace and Electronic Systems. Vol. 28, No. 3, 1992. pp. 817-828.
7. J. -P. Le Cadre, and C. Jauffret, "Discrete-time observability and estimability analysis for bearings-only target motion analysis. " IEEE Transactions on Aerospace and Electronic Systems. Vol. 33, No. 1, 1997. pp. 178-201.
8. Y. Oshman, and P. Davidson, "Optimization of observer trajectories for bearings-only target localization. " IEEE Transactions on Aerospace and Electronic Systems. Vol. 35, No. 3, 1999. pp. 892-902.
9. T. Bailey, "Constrained initialisation for bearing-only SLAM. " Proceedings of 2003 IEEE International Conference on Robotics & Automation. Taipei, 2003. pp. 1966-1971.
10. N. -M. Kwok, and G. Dissanayake, "Bearing-only SLAM in indoor environments using a modified particle filter. " Proceedings on Australasian Conference on Robotics and Automation. CD-ROM, Brisbane, 2003
11. N. -M. Kwok, and G. Dissanayake, "An efficient multiple hypothesis filter for bearing-only SLAM. " International Conference on Intelligent Robots and Systems. 2004.
12. A. Wald, Sequential analysis. Dover Publications Inc, NY. 1973.
13. ] J. -H. Kim and S. Sukkarieh, "Airborne Simultaneous Localisation and Map Building", Proc. 2003 IEEE Intl. Conf. on Robotics. Automation, Taipei, Taiwan, September 2003, pp. 406-411.
14. D. Aleksendric, C. Duboka, A Neural Model of Automotive Cold Brake Performance, FME Transactions (2007) 35, 9-14
15. M. T. Hagan, H. B. Demuth, M. Beale, Neural networks design, Boston, PWS, ISBN: 0-9717321-0-8, 1996.

Fuzzy Logic Autonomous Vehicle Navigation Fuzzy Control.