Abstract: The new generation of train control system for urban rail transit-Train Autonomous Circuit System (TACS) is a decentralized train autonomous collaborative control system based on train-train communication. Compared to the traditional communication based Train Control System (CBTCS), it is more efficient, flexible, and economical. To improve the operating efficiency of urban rail transit lines, an adaptive train operation time interval adjustment approach for TACS is proposed. Based on the existing architecture of TACS, a passenger flow data analysis system is proposed to monitor the real-time passenger flow of the entire line. When there is a peak passenger flow on the line, the train operation adjustment unit of the Automatic Train Supervision system (ATS) regenerates the train operation schedule which will trigger the wake-up of dormant trains to enter operating mode to increase carry capacity, and all online running trains exchange train operation data with each other based on the latest train operation schedule, thus adaptively adjusting the train operation time interval. The operational efficiency and economy of the line can be effectively improved by shortening the train operation time interval during peak passenger flow periods to increase the passenger carrying capacity of the line while extending the train operation time interval during low peak passenger flow periods to reduce energy consumption of line operation. This approach has a simple principle and is technically easy to implement, without affecting the existing structure and performance of the TACS .