考虑区域内可变车道与公交接驳的大型活动疏散优化模型

To address the challenges of low efficiency and high costs in large-scale crowd evacuations following large-scale events commonly seen in cities, this study proposes a bi-level optimized multi-modal evacuation model that integrates regional variable lane strategies with bus bridging. The framework aims to achieve integrated decision-making in road network supply and transport capacity allocation. The upper-level model minimizes the weighted average evacuation time by incorporating multiple variable lane strategies, including fleet configuration, lane allocation, lane reversal, and cross elimination. This model is optimized with the Artificial Bee Colony algorithm. The lower-level model, building upon the optimized network conditions from the upper level, minimizes total operating costs by dynamically planning bus dispatch, route connections, and fluctuating passenger demand. This model is solved with a Genetic Algorithm. To validate the proposed model and algorithms, a case study is conducted based on a concert held at the National Stadium. The results demonstrate that, compared to the initial scheme, the final solution obtained through the bi-level optimization model in this paper reduces the weighted average evacuation time in the variable lane area by 30.63 minutes, and lowers the total cost by 2.684 1 million yuan. This optimization significantly improves the evacuation efficiency and reduces the overall costs for bus operations, bus passengers, and private car users. This study verifies the effectiveness and economic benefits of coordinated optimization between variable lanes and bus bridging in managing large-scale events evacuations.