Evaluation and Application Algorithm of Artificial Intelligence Unmanned Vehicle Control Device Based on IoT Intelligent Transportation

With the rapid development of technology, unmanned vehicles have become a hot research topic in the field of intelligent transportation. Unmanned vehicles have many advantages, such as improving traffic efficiency, reducing traffic accidents, and reducing energy consumption. However, the controllability and safety of unmanned vehicles have always been a key issue in research. The Internet of Things can achieve information exchange and data sharing between vehicles, transportation facilities, traffic management centers, etc., providing real-time traffic and road condition information, and providing accurate data support for intelligent decision-making and path planning of unmanned vehicles. Therefore, the artificial intelligence unmanned vehicle control device based on IoT intelligent transportation has become an important research direction. This paper used deep reinforcement learning as the decision-making control algorithm, and designed a set of unmanned vehicle control system based on the DDPG (Deep Deterministic Policy Grad) algorithm, supplemented by meta DDPG algorithm, which is the knowledge of meta learning. Through the test of the simulation platform, it was concluded that the control system has good generalization. This study combined the Internet of Things and artificial intelligence algorithms, which has certain guiding significance for the development and application of unmanned vehicles in the future.