Automated Driving Licensing System Based on Wireless Sensor Networks and IoT

The advent of autonomous vehicles has revolutionized the automotive industry, offering promising advancements in safety, efficiency, and mobility. To integrate these autonomous vehicles into our society seamlessly, it is imperative to establish a robust licensing system that ensures the safe operation of automated vehicles on public roads. This paper presents an effective Automated Driving Licensing System (ADLS), a digital framework designed to regulate and license autonomous vehicles. The ADLS leverages cutting-edge technology, including artificial intelligence, machine learning, and secure data management, to evaluate and validate the capabilities of autonomous vehicle systems. Through a comprehensive assessment process, the system assesses the vehicle's ability to navigate various road conditions, respond to dynamic environments, and prioritize safety for passengers and other road users. The automated licensing issuance system ensures that only vehicles meeting predefined safety and performance criteria are granted licenses. Successful licensing is a testament to the vehicle's readiness for autonomous operation within specified geographic regions and under predefined conditions. The proposed system offers a comprehensive approach to safely integrate autonomous vehicles into our transportation ecosystem. Furthermore, the ADLS establishes a framework for continuous monitoring and updates, enabling ongoing assessments to keep pace with evolving technology and safety standards.