一种受QUBO启发的机场陆侧瓶颈诊断与动态调度优化计算框架
A QUBO-Inspired Computational Framework for Airport Landside Bottleneck Diagnosis and Dynamic Dispatch Optimization
- East China Jiaotong University（华东交通大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究针对机场陆侧高峰耦合拥堵问题，提出受QUBO启发的计算框架，通过5分钟状态模型与多指标诊断瓶颈，采用两种调度方案优化，在两大机场测试中显著缩减旅客队列，且具备鲁棒性。
AI中文摘要：
机场陆侧交通中心连接航站楼到达区与出租车、网约车、私家车、公交车、地铁服务、停车设施及航站楼区域道路。高峰到达客流会在旅客队列、车辆队列、接客泊位、存储区域及接入道路间引发耦合拥堵。本研究提出一种受QUBO启发的计算框架，用于该场景下的瓶颈诊断与动态调度优化。以上海浦东国际机场、杭州萧山国际机场为案例机场，构建了一个5分钟间隔的状态模型，关联旅客到达量、车辆供给量、接客泊位服务效率、车辆存储容量及道路通行能力。瓶颈诊断采用服务强度、道路需求饱和度、瓶颈发生频率、队列严重程度、影子价格杠杆效应及综合拥堵严重程度指数作为指标。在一致的需求输入下测试了两种调度方案：有限动作模型预测控制与受二次无约束二元优化启发的模拟退火算法。在强高峰基准场景下，受QUBO启发的方法将上海浦东机场的最终旅客队列规模从3445人降至2477人，杭州萧山机场的最终旅客队列规模从2053人降至1482人。案例结果显示两机场的主导瓶颈不同：上海浦东机场受道路饱和度影响更大，杭州萧山机场受接客泊位服务效率影响更大。在需求、供给、服务、道路通行能力、方式分担及随机噪声扰动下的鲁棒性测试表明，在测试的不确定性水平下，队列缩减效果得以保持。
英文摘要：
Airport landside traffic centers connect terminal arrivals with taxis, ride-hailing vehicles, private cars, buses, metro services, parking facilities, and terminal-area roadways. Peak arrivals can create coupled congestion across passenger queues, vehicle queues, pickup berths, storage areas, and access roads. This study proposes a QUBO-inspired computational framework for bottleneck diagnosis and dynamic dispatch in this setting. Shanghai Pudong International Airport and Hangzhou Xiaoshan International Airport serve as case airports. A five-minute state model links passenger arrivals, vehicle supply, pickup berth service, vehicle storage, and road capacity. Bottleneck diagnosis uses service intensity, road demand saturation, bottleneck frequency, queue severity, shadow-price leverage, and a composite congestion severity index. Two dispatch schemes are tested under consistent demand inputs: finite-action model predictive control and quadratic-unconstrained-binary-optimization-inspired simulated annealing. In the strong-peak baseline scenario, the QUBO-inspired method reduces the final passenger queue from 3445 to 2477 passengers at Shanghai Pudong and from 2053 to 1482 passengers at Hangzhou Xiaoshan. Case results indicate different dominant bottlenecks. Shanghai Pudong is more affected by road saturation, whereas Hangzhou Xiaoshan is more affected by pickup berth service. Robustness tests under demand, supply, service, road-capacity, modal-share, and random-noise perturbations show retained queue-reduction benefits under the tested uncertainty levels.
