QUBO-Inspired Framework for Airport Landside Congestion Management

A novel computational framework, drawing inspiration from Quadratic Unconstrained Binary Optimization (QUBO), has been introduced to identify bottlenecks and enhance dynamic dispatch in airport landside traffic centers. These centers facilitate connections between terminal arrivals and various transport options, including taxis, ride-hailing services, private vehicles, buses, metro systems, parking areas, and terminal roadways. Peak arrival times can lead to intertwined congestion among passenger lines, vehicle queues, pickup zones, storage spaces, and access routes. The framework was evaluated through case studies at Shanghai Pudong International Airport and Hangzhou Xiaoshan International Airport. A five-minute state model integrates passenger arrivals, vehicle availability, pickup berth operations, vehicle storage, and roadway capacity. Bottleneck identification utilizes metrics such as service intensity, road demand saturation, and a composite congestion severity index. Two dispatch strategies were analyzed with steady demand inputs: finite-action model predictive control and quadr... (truncated). The research can be found on arXiv with the identifier 2608.08632.