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In recent years, along with the economy booming development, accelerate the process of the modernization in our country, traffic infrastructure to push. Affected by Internet big data technology change, the traditional subway fare collection system cannot meet the high traffic and large data stream processing requirement for high strength work. In daily practice applications, the traditional subway fare collection system often appear check-in recognition rate is low, the ticket information processing slow response speed, more personnel multitasking operating problem of poor accuracy of execution. Aiming at the above problems, combining the resources of the large data and computing power, metro automatic fare collection system under big data environment is designed. Using big data real-name widely processing engine (VBDKG), multiplex section arithmetic module (ICGRU) and dynamic identity comparison algorithm (DBTDE) for the problem of the traditional metro automatic fare collection system is solved. Through the simulation test proves that the proposed large data environment design of metro automatic fare collection system with strong practicability and maneuverability. At the same time, higher processing accuracy, stable operation.