VEHICLE CRASH AVOIDANCE USING ADAPTIVE NEURAL-FUZZY INFERANCE SYSTEM
- E V VISWANATH KUMAR
- G KALAIMAGAL
MEMS, Gyroscope, ANFIS, UART, ADC, SMAC protocol, Ultrasonic Sensor.
Vehicle crashes are consider to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one need to consider various areas of research. For this reason, we simply analysis and improve the modeling process. In this project , a novel adaptive neural fuzzy inference system(ANFIS based) approach is implemented to reconstruct kinematics for colliding vehicles. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different types of collisions than the one which was used in the training stage. Finally, the simulation outcomes are compared with the results obtained by applying different modeling techniques. The reliability of the proposed method is evaluated.
E V VISWANATH KUMAR, G KALAIMAGAL. "VEHICLE CRASH AVOIDANCE USING ADAPTIVE NEURAL-FUZZY INFERANCE SYSTEM".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 2, pp.1364-1369, URL :https://rjwave.org/ijedr/papers/IJEDR1402008.pdf
Volume 2 Issue 2
Pages. 1364-1369
