With the rapid development of social economy and urbanization in China, the relationship between professional and residential space of urban residents is constantly changing. Under the background of the imbalance of urban functional structure, the traffic congestion problem is becoming more and more serious, and the travel demand of residents' rail transit is increasing. Taking Beijing as an example, based on public transport big data, this paper uses k-means clustering to discuss the passenger travel law under the network structure of rail transit in detail, and systematically analyzes the relationship between the travel law and the urban functional structure between the imbalance of duty and housing and excessive commuting, which provides theoretical support for the collaborative optimization of passenger flow control and operation scheme when urban rail transit is saturated under the impact of large passenger flow.

CICTP