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To travel securely on roads, traffic signs are very important. The main cause of road accidents is laxity in viewing the traffic signboards and analysing them wrongly. To avoid all these problems, the new system is implemented. This system helps in identifying the traffic sign and sends a voice command to the driver, so that the driver will take necessary actions to travel safely. The system is trained by using Convolutional Neural Network (CNN/ConvNet), helps in classification and recognisation of traffic sign images. To make the system more accurate, a particular dataset is taken and trained by defining a set of classes. The German Traffic Sign Recognition Benchmark dataset was used for classification of sign boards,it contains more than 40 classes and more than 50000 images of traffic signs. After detecting the sign, a voice command is sent to notify the driver and aware him/her to follow the necessary rules on the road. The main aim of this system is safe and secure travelling and the lives of the people. [ABSTRACT FROM AUTHOR]