Objective In traditional CBTC （communications-based train control） systems, it is necessary to rely on the clearance status of wayside secondary detection equipment to identify non-communicating or faulty trains, while using head screening and tail screening methods to filter cleared sections, leading to complex operations, low efficiency, and significant operational impacts. To achieve rapid and automatic screening of all line trains without relying on secondary detection equipment, a TACS （train autonomous control system） train screening method based on a train set model is proposed.

Method Based on the feature that each train object on the line possesses a unique identifier, a train set model is established to analyze the correlation between the train set and line resource allocation, and demonstrate the train screening principle of determining line section vacancy for trains without allocated line resources. Boundary intrusion detection technology is utilized to calculate whether unidentified trains enter the TACS zone, combined with manual screening methods to identify non-communicating trains.

Result & Conclusion Through the analysis of train screening under normal and degraded scenarios, it is verified that TACS train automatic screening can be achieved without deploying secondary detection equipment on the line, even in the presence of non-communicating or faulty trains. On the premise of ensuring safety, the method improves the efficiency of TACS train screening, enables rapid fault recovery for TACS, and enhances overall operational efficiency.