Traffic Management Optimization via Iot-Enhanced Cooperative Vehicle-Infrastructure Systems

Under the trend of continuous expansion of urban areas and increasing number of vehicles, the traditional transportation system has been unable to cope with various complex situations, and the problem of insufficient information exchange has emerged. This study is based on the cooperative vehicle-infrastructure system (CVIS) of the Internet of Things (IoT)-enhanced intelligent model, aiming to solve the problem of insufficient information exchange in the existing intelligent transportation system under dynamic traffic conditions. Thus, power management, intelligent driving ability, and driving comfort and safety can be improved. Through the application of IoT technology, a CVIS is established, which enables efficient information exchange between vehicles and infrastructure by constructing advanced IoT architectures, and utilizes reinforcement learning models to optimize system responses and driving strategies. The experimental results show that the system can maintain an effective accelerated response of the vehicle, even under heavy loads (up to 2000 kg) and complicated road conditions, with the fastest response time of 15.9 seconds. In addition, the system remarkably improves driving stability, especially in tests conducted on slippery roads and uphill segments. Regarding safety and security, the system achieved a commendable command recognition accuracy of about 100%. Moreover, integrated intelligent algorithms help reduce overall energy consumption while maintaining system performance. These results highlight the critical role of IoT technology in promoting the responsiveness and safety of intelligent vehicle systems.