交通运输系统工程与信息

交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (2): 159-168.DOI: 10.16097/j.cnki.1009-6744.2026.02.015

• 系统工程理论与方法 • 上一篇    下一篇

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

田琼*1,2 ，王铭阳1,3   

  1. 1. 北京航空航天大学，经济管理学院，复杂系统分析与管理决策教育部重点实验室，北京100083； 2.杭州市北京航空航天大学国际创新研究院（北京航空航天大学国际创新研究院），杭州311115； 3. 北京航空航天大学，中法工程师学院，北京100191
  • 收稿日期:2025-11-04 修回日期:2025-11-23 接受日期:2025-12-09 出版日期:2026-04-25 发布日期:2026-04-20
  • 作者简介:田琼（1981—），男，河北廊坊人，教授。
  • 基金资助:
    国家重点研发计划(2023YFE0115600)；国家自然科学基金(72288101)。

Optimization Model for Large-scale Events Evacuation Considering Regional Variable Lane Strategies and Bus Transfer

TIAN Qiong*1,2, WANG Mingyang1,3   

  1. 1. MOE Key Laboratory of Complex System Analysis and Management Decision, School of Economics and Management, Beihang University, Beijing 100083, China; 2. Hangzhou International Innovation Institute of Beihang University, Hangzhou 311115, China; 3. Sino-French Engineer School, Beihang University, Beijing 100191, China
  • Received:2025-11-04 Revised:2025-11-23 Accepted:2025-12-09 Online:2026-04-25 Published:2026-04-20
  • Supported by:
    National Key Research and Development Program of China (2023YFE0115600)；National Natural Science Foundation of China (72288101)。

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摘要： 针对城市中常见的大型活动散场引发的大规模客流疏散效率低下、成本高的难题，本文提出考虑区域内可变车道与公交接驳的双层优化多模式疏散模型，以实现路网供给与运力分配的一体化决策。模型上层以最小化加权疏散时间为目标，融合车队配置、车道分配、车道反转和交叉消除的多重可变车道策略，采用人工蜂群算法进行优化；下层基于上层优化的路网条件，以最小化总运营成本为目标，考虑接驳公交线路派出，线路连接关系，待输运乘客需求量动态变化，采用遗传算法进行优化。本文以在国家体育场举办演唱会为实例验证模型和算法的有效性。结果表明：与初始方案相比，本文模型进行双层优化所得最终方案，可变车道区域的加权平均疏散时间减少30.63min，总成本下降268.41万元，极大提高了疏散效率，降低了公交运营、公交乘客和私家车乘客总成本。本文验证了可变车道与公交接驳协同优化在应对大型活动疏散中的有效性与经济性。

关键词: 城市交通, 大型活动疏散, 双层优化, 可变车道, 公交接驳, 遗传算法

Abstract: 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.

Key words: urban transportation, large-scale event evacuation, bi-level optimization, reversible lane, bus transfer, genetic algorithm

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