Traffic big data is the most basic condition for solving urban traffic problems. It is an important guarantee for formulating macro-city traffic development strategy and construction planning. And it is also an important guarantee for carrying out micro-road traffic management and control. In view of the characteristics of intelligent transportation system such as fast data generation, high real-time performance and large amount of data, this paper constructs a real-time traffic data processing platform based on the combination of Spark Streaming and Apache Kafka to process the data collected by dual base stations. Using time window mechanism to get data from Kafka, and process the data to the database according to the rules. In this study, the system architecture and internal structure of the platform are introduced in detail, and the real-time processing capability of the system is verified through experiments, which can be applied under large-scale and high-concurrency data flow.