Intelligent Transportation Systems (ITS) have become a crucial technology for solving road traffic problems and an essential component of urban sustainable development. With the acceleration of urbanization and the rapid increase in the number of motor vehicles, traffic congestion is becoming increasingly severe. Statistics show that the number of motor vehicles in China reached 340 million in 2018, increased to 320 million by the end of 2019, and is expected to reach 480 million by the end of 2020. Meanwhile, the per capita urban road area in China is less than 10 m2, only one-sixth of that in the United States and one-quarter of that in Japan, which significantly increases the traffic pressure. To address this challenge, the nation has adopted measures such as “vigorously developing public transportation” and “building intelligent transportation.” However, relying solely on infrastructure construction is insufficient to meet the demand, necessitating the enhancement of traffic management through advanced technological means. Based on this, this paper constructs an intelligent transportation system simulation platform to test and optimize system performance. This platform not only simulates different traffic management schemes to verify their effectiveness but also proposes optimization strategies through data analysis to achieve efficient and orderly traffic flow. Specific case analyses validate the practicality and effectiveness of the simulation platform in solving traffic congestion problems, providing new ideas and methods for the future development of intelligent transportation systems.