为了准确评定重大交通基础设施项目组织韧性等级，提升项目应对突发事件及风险的能力，引入韧性理论界定重大交通基础设施项目组织韧性的内涵。以韧性演进过程中的抵抗能力、吸收能力、恢复能力、适应能力为核心，结合高速公路线性工程环境暴露度高、多主体协同等特征，从人员、设备、管理、环境、应急等5个方面构建组织韧性评估体系。基于变权物元可拓理论，引入贴近度判定准则替代最大隶属度原则，构建改进的项目组织韧性评价模型，以提高韧性等级判定的准确性。通过模型评价结果识别影响项目组织韧性的关键指标，包括智能监测设备覆盖率、事故经验学习能力、信息反馈效率等，并从全周期管理、设备技术创新、专业人才培养、环境防御体系和应急联动机制等5个方面凝练提出韧性提升策略。最后，选取某市西二绕城高速公路项目进行实证应用。结果表明：该高速项目的组织韧性等级为Ⅱ级，属于较高韧性等级，但有偏向Ⅲ级中等韧性的趋势，评价结果与实际工程状况基本吻合，验证了模型的有效性。研究构建的融合智能建造要素的韧性指标体系，以及改进物元可拓模型中的权重动态调整和判别准则，可为重大交通基础设施项目的韧性评估与管理提供理论参考和实践工具。

To accurately assess the organizational resilience grade of major transportation infrastructure projects and enhance their capability to cope with emergencies and risks, this paper defines the connotation of organizational resilience for such projects based on resilience theory. Focusing on the four core capacities in the resilience evolution process—resistance, absorption, recovery, and adaptation—and considering the characteristics of highway linear projects such as high environmental exposure and multi-agent collaboration, an organizational resilience evaluation system is constructed from five dimensions: personnel, equipment, management, environment, and emergency response.Based on the variable-weight matter-element extension theory, the closeness-degree criterion is introduced to replace the maximum membership degree principle, and an improved project organizational resilience evaluation model is constructed to enhance the accuracy of resilience grade determination. Based on the evaluation results, key indicators affecting project organizational resilience are identified, including intelligent monitoring equipment coverage rate, accident experience learning capability, and information feedback efficiency. Resilience enhancement strategies are summarized from five aspects: full lifecycle management, equipment technology innovation, professional talent development, environmental defense systems, and emergency linkage mechanisms. Finally, the West Second Ring Expressway project in a certain city is selected for empirical application. The results show that the organizational resilience grade of this expressway project is Level Ⅱ, indicating a relatively high level, but with a tendency toward Level Ⅲ. The evaluation outcome is generally consistent with the actual project conditions, verifying the model′s effectiveness. The study constructs a resilience indicator system incorporating smart construction elements and improves the dynamic weight adjustment and discrimination criteria of the matter-element extension model, providing theoretical references and practical tools for resilience evaluation and management of major transportation infrastructure projects.