Trends in Applied Sciences Research1819-35792151-7908Science International10.3923/tasr.2014.246.253SelmaBoumediene ChourqauiSamira 5201495This study deals with a path planning and intelligent control of an autonomous vehicle which should move safely in its road partially structured. This road involves a number of obstacles like speed bump, traffic lights and other vehicles. In this study the Neural Networks-based technique (NN) is described to solve the motion-planning problem in Unmanned Vehicle (UV) control. This is accomplished by choosing the appropriate inputs/outputs and by carefully training the NN. The network is supplied with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. The network has been trained with a set of strategic input-output. The results show the effectiveness of the technique used, the Unmanned Vehicle (UV) drives around avoiding obstacles.]]>Andrievsky, B. and A. Fradkov,20022002pp: 290291Astrom, K.J. and B. Wittenmark,1989Banks, W. and G. Hayward,20012001Cordon, O., F. Gomide, F. Herrera, F. Hoffmann and L. Magdalena,2004141531Cuesta, F. and A. Ollero,2005Pages: 204Pages: 204Doitsidis, L., K.P. Valavanis, N.C. Tsourveloudis and M. Kontitsis,20042004pp: 40414046Li, Y., N. Sundararajan and P. Saratchandran,20013712931301Ren, W. and R.W. Beard,20032003pp: 39243929Martinez, R., O. Castillo and L.T. Aguilar,200917921582174Schumacher, C.J. and R. Kumar,20002000pp: 849853Selma, B. and S. Chouraqui,2012397107Sam Ge, S. and F.L. Lewis,2006Pages: 736Pages: 736Verbruggen, H.B., H.J. Zimmerman and R. Babuska,19992nd Edn.,Pages: 352Pages: 352