How to Reduce the Number of Inspectors: Operation Mode and Modeling Simulation of Centralized Image Recognition in Railway Passenger Security Inspection

Abstract

Security inspection is an essential step for passengers entering railway stations in China. Under the existing security inspection operation mode, each X-ray machine needs an image inspector to recognize the X-ray image, which poses the issue of resource optimization for inspectors. Based on the networking of security inspection X-ray machines, an innovative centralized image recognition (CIR) operation mode for railway security inspections is proposed, and it is worth noting that network and device failures are risk factors for this mode. The method for assigning image recognition personnel is designed to reduce labor force needed for security inspection. Using a combination of agent-based modeling method and computer simulation technology, the four elements of passengers, security inspection X-ray machines, X-ray image inspectors, and secondary baggage inspection personnel are modeled, and CIR indicators to study the effectiveness of the operation are designed. Based on the real departing passenger data of the Zhangjiakou section of the Beijing Zhangjiakou Line in China, simulation is conducted in two scenarios: large passenger flow and small passenger flow. The research is conducted from three aspects: operational efficiency, travel experience, and system complexity. Experiments have shown that, with a slight increase in passenger waiting time, the average number of X-ray image inspectors is reduced by more than 70% compared with the existing operation mode. The best pick-up location for passengers is related to passenger flow. The proposed model can analyze the effectiveness of CIR operation mode and provide decisive support for the application of CIR operation mode.