This paper provides an efficient way to design an automatic car braking system using Fuzzy Logic. The system could avoid accidents caused by the delays in driver reaction times at critical situations. The proposed Fuzzy Logic Controller is able to brake a car when the car approaches for an obstacle in the very near range. Collision avoidance is achieved by steering the car if the obstacle is in the tolerable range and hence there is no necessity to apply the brakes. Another FLC (which is cascaded with the first FLC for collision avoidance) implements the Anti-lock Braking capability during heavy braking condition. Thus the system is made intelligent since it could take decisions automatically depending upon the inputs from ultrasonic sensors. A simulative study is done using MATLAB and LabVIEW software. The results obtained by the simulation model are compared with the existing system and the proposed model conveys a satisfactory result which has high consumer acceptance. ATMega controller is used for implementation of the proposed system.

1. David Fernandez Liorca, Vicente Milanes, Ignacio Parra Alonso and Miguel Gavilan (2011) 'Autonomous pedestrian collision avoidance using a fuzzy steering controller', IEEE Transactions on Intelligent Transportation Systems, Vol. 12, No. 2, pp. 390-401.
2. Chuting Mi, Hui Lin and Yi Zhang (2009) 'Iterative learning control of antilock braking of electric and hybrid vehicle', IEEE Transactions on Vehicular Technology, Vol. 54, No. 2, pp. 486-494.
3. Ayman A. Aly (2010) 'Intelligent fuzzy control for anti-lock braking system with road-surfaces identifier', Proceedings of the IEEE International Conference on Mechatronics, pp. 699-705.
4. Shrey Modi, Yingzi Lin, Zhang W. J and Yang G. S (2012) 'A driver-automation system for brake assistance in intelligent vehicles', Proceedings of the 10th IEEE International Conference on Industrial Informatics, pp. 446-451.
5. Vijayakumar Ch, Pavan Kumar N, Prathiba J and Vijay Kumar K (2013) 'Sensors based automated wheel chair', Proceedings of the IEEE International Conference on Green Computing, Communications and Conservation of Energy, pp. 439-443.
6. Hasan K. M, Sabina Khan, Sameen Javaid and Asif Raza (2010) 'A low cost microcontroller implementation of fuzzy logic based hurdle avoidance controller for a mobile robot', Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology, pp. 480-485.
7. Bo Lu, Yu Wang, Jing-Jing Wu and Jin-Ping Li (2010) 'Anti-Lock braking system design based on improved fuzzy PID control', Proceedings of the IEEE International Conference on Natural Computation, pp. 62-65.
8. Ghulam Abbas and Muhammad Usmah Asad (2011) 'Comparative analysis of zero-order sugeno and mamdani fuzzy logic controllers for obstacle avoidance behavior in mobile robot navigation', Proceedings of the IEEE International Conference on Current Trends in Information Technology, pp. 113-119.
9. Hui Lin and Channxue Song (2011) 'Design of a fuzzy logic controller for abs of electric vehicle based on amesim and simulink', Proceedings of the IEEE International Conference on Transportation, Mechanical and Electrical Engineering, pp. 779-782.
10. Izzuddin Muhammad Iqbal, Muhamad Hariz Rosli, Mohd Azlan Abu and Zainudin Kornain (2012) 'Automated car braking system using neural network system via labview environment', Proceedings of the IEEE International Conference on Open Systems, pp. 1-6.
11. Kai Zhou, Xudong Wang, Chao Zhang and Jian Liu (2010) 'Data acquisition system based on labview for abs dynamic simulation test stand', Proceedings of the IEEE International Conference on Information and Automation, pp. 2214-2218.
12. Samuel John and Jimoh O. Pedro (2013) 'A comparative study of two control schemes for anti-lock braking systems', Proceedings of the 9th IEEE Asian Control Conference, pp. 1-6.

Collision Avoidance Anti-lock Braking System (abs) Slip Ratio Simulation Interface Toolkit (sit).