Published Paper Details:

Previous innovative driving technologies have made incredible progress in individual aspects such as lane recognition, traffic sign recognition, and object recognition etc. These features, nonetheless though promising, it worked independently in autonomous driving. Although lane detection systems provided accurate vehicle stops, lane detection signs interpreted road signs, and detection systems detected obstacles, the lack of integration gave them limiting the ability to make joint contextual decisions This has led to operational deficiencies and security concerns. Our project marks a breakthrough in the autonomous driving landscape by developing an integrated vision-based autonomous driving system that integrates these important features. Road detection, vehicle sign recognition and object recognition are seamlessly integrated to work in harmony to provide a comprehensive and intelligent driving experience This integration facilitates real-time data fusion to display vehicles under and behave in synchrony with each other. Lane identification It ensures learning accuracy, traffic sign recognition provides important regulatory information, and protects sights from collisions. The combination of these features enhances the overall safety, performance, and reliability of autonomous vehicles.