Road signs are required to ensure a safe and secure flow of traffic. Laxity in seeing traffic signs and displaying them inaccurately is a major cause of road accidents. The proposed system assists in identifying traffic signs and alerting the driver so that he or she may make the appropriate selections. Convolutional Neural Network (CNN) is used to train and test the suggested system, which aids in traffic sign picture identification and categorization. To improve the accuracy of a dataset, a set of classes is developed and trained on it. The German Traffic Sign Benchmarks Dataset was utilised, which contains 51,900 pictures of traffic signs divided into 43 categories. The execution precision is around 98.52 percent.The suggested system includes a segment in which the motorist is notified to nearby traffic signs, which helps them understand what laws to follow on the road. A voice alarm is broadcast over the speaker once the sign is detected, alerting the driver. The suggested system also includes a segment in which the vehicle driver is notified to nearby traffic signs, which assists them in understanding the regulations that must be obeyed to guarantee maximum safety. The goal of this system is to protect the driver, passengers, and pedestrians in the vehicle..

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