Robustness assessment of demand-oriented transportation networks: A community structure methodology

Assessing the robustness of Demand-Oriented Transportation Networks (DOTNs) is essential to ensure their stability and sustainable functioning. With swift economic development and rapid urbanization, TNs are expanding significantly in scale. However, most existing research on large-scale TNs analyzes robustness from a topological perspective, overlooking the heterogeneity of passenger travel demand distribution. To address this issue, this paper proposes a novel community structure methodology to assess the robustness of DOTNs from the demand perspective. A dual-layer model, comprising the Physical Layer (PL) and the Demand Layer (DL), is constructed to describe the topological structure and demand characteristics of DOTNs. Considering the large size of DOTNs, a combined structure of the Inter-community graph and Intra-community graph (ECG-ACG) is generated through the community detection of the DOTN. Based on this structure, a dual-phase ECG-ACG inverse reinsertion is proposed to comprehensively determine the optimal attack sequence for the entire DOTN. Additionally, an incremental calculation method is introduced to improve the computational efficiency of calculating the incremental passenger travel demand of removed nodes/edges. Experiments conducted on eight real TNs with various sizes and transportation modes demonstrate the effectiveness and scalability of the proposed methodology.