A Method for Identifying Key Links Based on Path Redundancy Under Time-Varying Conditions

The study focuses on a model for identifying critical road links based on path redundancy in road networks. Path redundancy enhances efficiency for daily travel and provides crucial alternative routes during emergency situations. This model comprehensively considers time-varying factors in the road system, including origin-destination (OD) demand, OD pair, and road congestion. By analyzing time-varying factors for each period, the path redundancy of the road network is calculated. Furthermore, combining the weights of each period with their corresponding path redundancy yields the expected value of path redundancy, facilitating accurate identification of critical links. To address the computational challenge of solving for large-scale path redundancy, a reconstruction of the urban road network structure is performed, enabling the use of maximum flow and minimum cost flow algorithms, which have polynomial time complexity, for iterative solutions. The effectiveness and applicability of the model and algorithm are verified through practical application in the Pinglu Canal bridge reconstruction project. Results reveal the impact of the bridge group's removal and reconstruction on the redundancy of the road network in Qinzhou. Changes in OD pair path redundancy are highlighted, providing a basis for refined traffic management measures before and after construction. In terms of computational efficiency, the proposed algorithm shows a significant advantage over Gurobi. The computation time improves by 17.90 times, demonstrating its suitability for large-scale urban road networks. This paper can be targeted to enhance the resilience of key road sections, thereby contributing to the construction of a more resilient urban road transport system.