The current technology revolution in automobile industry is the autonomous vehicle wherein the vehicle without any intervention from the human driver responds to all kind of external conditions and performs all necessary functions that a human driver would perform while driving. Traffic sign identification is a crucial task in an autonomous driving system and even a minute misinterpretation could turn into a fatal one. This paper proposes a CNN based image classification which specifically uses pre-trained feature generated neural networks present in GoogleNet. GoogleNet is a CNN which recognizes the traffic signboards present by the roadside and sends the control signal to a microcontroller (Arduino Board) which controls the speed and the steering of the vehicle. The implemented CNN based automatic speed and steering control has been verified with a greater accuracy. The work presented in this paper leads towards the development of smart and sustainable cities under the Smart Cities Mission of India.

No abstract