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In the era of big data, the global data is growing explosively. The huge growth rate makes data processing and storage difficult, especially in the field of transportation. Based on the above background, this paper aims to study the autonomous coordinated control strategy for the complex process of traffic information physical fusion system based on big data. In this paper, the information physical fusion system is applied to the modern transportation system, and it is used to realize the high integration of computation, communication and control. Realize the independent and coordinated control of the transportation system. This paper proposes an autonomous traffic management mechanism based on multi-agent CPS system. In view of the instability and untimely of the original control strategy, a new traffic optimization control strategy conflict reduction control strategy is proposed. In order to solve the complexity of traffic system, the generation method of CPS autonomous control strategy based on multi-agent is studied and analyzed. Through the evaluation and verification of the conflict reduction control strategy and the online simulation of the incremental data synchronization strategy, it can be seen that the inconsistency ratio curves of message quantity and byte transmission quantity are always kept at a relatively low level, 1% and 2%, respectively. During the whole experiment, the average number of inconsistent messages and byte transmission of the agent are ideally controlled at 1.2 messages / train and 0.5kb/train.

Autonomous Coordinated Control Strategy for Complex Process of Traffic Information Physical Fusion System Based on Big Data