面向韧性运营的城市轨道交通调度指挥系统数字化转型路径与核心技术体系

Digital Transformation Path and Core Technical System of Urban Rail Transit Dispatching and Command Systems for Resilient Operation

  • 摘要:
    目的 作为城市轨道交通运营“大脑”的行车调度指挥系统,在网络化运营环境下暴露出安全保障不足、协同决策困难、资源配置低效等局限性,亟须构建具有感知、分析、决策、执行、学习能力的数字化调度指挥体系,以提升城市轨道交通的运营韧性和服务品质。
    方法 首先,界定韧性运营内涵,分析数字化技术赋能作用。其次,提出“信息-流程-业务-决策”4层递进的数字化转型路径。再次,构建涵盖风险感知、运行优化、应急决策、协同控制、仿真预演的关键技术体系。最后,通过运营线路管养维护施工安全管控案例,验证了施工天窗精准规划、管养作业实时安全管控、施工经验知识沉淀等数字化应用效果。
    结果及结论 数字化转型使调度指挥系统实现从“经验驱动”向“数据驱动”的根本转变,呈现感知全面化、分析智能化、决策科学化、执行自动化特征。案例表明,通过“感知-分析-决策-执行”闭环体系,能有效提升运营线路管养维护施工期间的行车安全管控水平。

     

    Abstract:
    Objective As the "brain" of urban rail transit operations, train dispatching and command systems expose limitations such as insufficient safety assurance, difficult collaborative decision-making, and inefficient resource allocation in networked operation environments. There is an urgent need to construct a digital dispatching and control system with perception, analysis, decision-making, execution, and learning capabilities, so as to enhance the operational resilience and service quality of urban rail transit.
    Method First, the connotation of resilient operation is defined, and the enabling role of digital technologies is analyzed. Second, a four-layer progressive digital transformation path of "information–process–business–decision" is proposed. Third, a five-part key technical system covering risk perception, operation optimization, emergency decision-making, collaborative control, and simulation rehearsal is constructed. Finally, through a case study on safety control of maintenance and construction in operational line management, the digital application effects—such as precise planning of construction windows, real-time safety control of maintenance operations, and the accumulation of construction experience and knowledge—are verified.
    Result & Conclusion Digital transformation enables dispatching and command systems to achieve a fundamental shift from "experience-driven" to "data-driven" operation, presenting the characteristics of comprehensive perception, intelligent analysis, scientific decision-making, and automated execution. The case study demonstrates that through the closed-loop system of "perception–analysis–decision-making–execution", the safety control level of train operations during maintenance and construction periods on operational lines can be effectively improved.

     

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