T/XZBX 0084-2025 Urban rail transit collaborative intelligent scheduling system technical guideline
T/XZBX 0084-2025 Urban rail transit collaborative intelligent scheduling system technical guideline
Basic Information
Scope
With the acceleration of urbanization and the continuous expansion of rail transit networks, rail transit systems are facing challenges such as frequent peak passenger flows, complex line intersections, and ever-increasing demands for operational efficiency and safety management. Traditional manual scheduling and decentralized control models have become difficult to meet the needs of efficient, safe, and intelligent development of modern rail transit. The collaborative intelligent scheduling system integrates cutting-edge technologies such as artificial intelligence, big data, cloud computing, and the Internet of Things to achieve real-time perception and analysis of the operating status of rail transit trains, passenger flow dynamics, and equipment conditions. It can provide intelligent decision-support for the operations command center and promote the rapid issuance and accurate execution of scheduling instructions. This system not only effectively improves operational efficiency and train punctuality, but also provides rapid response measures in the event of emergencies and abnormal situations, reduces safety risks, and enhances passenger travel experience. At present, China has carried out a number of demonstration applications in the field of intelligent scheduling for rail transit, but there is still a lack of unified standards in terms of technical systems, system architectures, interface standards, data sharing, and safety management. Therefore, it is necessary to develop a systematic technical guide. This document aims to provide technical basis and practical guidance for the design, construction, operation, and maintenance of collaborative intelligent scheduling systems for rail transit, clarify the system's functional positioning, overall architecture, key technical requirements, and operational management norms, promote the transformation of rail transit scheduling from "manual-driven" to "intelligent-driven", and provide support for the development o