Scenario Modeling for Urban Road Emergency Management: A Cognitive Digital Twin–Based Method

The cognitive digital twin (CDT) concept provides a promising way to organize and integrate the full life-cycle data of urban road emergency scenarios, as well as facilitate scenario deduction and prediction. The construction of twin models constitutes the prerequisite for the practical implementation and application of CDT. However, the existing research on emergency scenario twin modeling falls short in providing a unified modeling method that comprehensively captures the multidimensional characteristics of scenario elements. This deficiency, coupled with inadequate analysis of interelement interactions and constraints posed by semantic inconsistencies and interoperability among twin models, hampers the accurate mapping of physical scenarios and their evolution dynamics. In response to the multielement, uncertainty, and dynamic nature of urban road emergency scenarios, this paper proposes a CDT modeling method for urban road emergency scenarios. First, the definitions of element-level and scenario-level twin models are elucidated in three dimensions—geometry, attribute, and behavior—in conjunction with resilience theory. Second, a modeling method based on SysML and ontology is proposed for twin models at different levels, and a SysML2Ontology transformation tool is developed to enable the systematic construction of emergency scenario cognitive digital twin (ESCDT). Furthermore, a CDT framework for urban road emergency management centered on twin models is introduced. Finally, the North-South Elevated Road in Shanghai, China, is used as the engineering application object. The feasibility of our modeling methodology is validated through a case study, which involves the construction of the ESCDT for a collision accident. The model can be further utilized for emergency scenario deduction, ultimately elevating the effectiveness of emergency management.