Traffic Sign Detection and Recognition Systems for Autonomous Vehicle Software Development

The current transportation systems require real-time detection and classification of road signs for ensuring safe and effective driving. It introduces a car-mounted camera system which detects traffic signs and applies Vision Transformers (ViTs) to identify road signs between stop signals and right turn directions as well as speed limit indicators. The system operates smoothly together with Google Maps through its utilization of geospatial information to boost navigation accuracy. Real-time traffic sign classification happens through road images captured by the camera and processed by a model built from ViT-based global feature extraction architecture. The method uses self-attention from ViTs to enhance operational outcomes when dealing with diminished visibility during conditions such as partial shading and lighting modifications as well as weather disturbances. Definitive traffic signals stored through Google Maps enable precise navigational notices for the driver. The system demonstrates excellent detection and classification precision together with quick response times which makes it suitable for live infrastructure deployment. Vision Transformers working with mapping technology decreased roadway safety hazards by delivering immediate accurate predictions about upcoming road traffic signs. Future iterations of this proposed system will add identification support for additional traffic signs alongside monitoring changes that occur during driving.