Modeling and Assessment of Airport Capacity and Operational Bottlenecks

Research Problem

Airport capacity is not a single fixed number. The number of aircraft an airport can accommodate depends on runway configuration, traffic mix, separation requirements, weather, congestion, and the operational conditions prevailing at different times of the day.

Airport managers must therefore balance two competing objectives: accommodating traffic demand while avoiding excessive delays and unstable operations. Setting capacity too conservatively underutilizes infrastructure, while setting it too aggressively can generate queues, delay, and operational unreliability.

Reliable methods are needed to identify emerging bottlenecks, predict congestion, and support capacity declaration and planning decisions.

Contributions

Our research combines simulation, queueing models, machine learning, and optimization to support airport capacity management.

Key contributions include:

• A unified framework for selecting appropriate delay-prediction methods across different airport planning horizons
• Data-driven methods for extracting local airport delays from ADS-B trajectory data
• Hybrid queueing and machine-learning models that capture congestion together with weather, temporal, route, and propagated-delay effects
• Large-scale empirical analysis using data from Singapore, Hong Kong, Kuala Lumpur, and Bangkok
• Integration of predictive analytics with prescriptive models for capacity declaration and slot allocation
• Multi-objective methods that expose the trade-offs between accepted demand, slot displacement, and expected operational delay

Selected Publications

• Delay Predictive Analytics for Airport Capacity Management
  Ribeiro, N. A., Tay, J., Ng, W., & Birolini, S. (2025). Transportation Research Part C: Emerging Technologies, 171, 104947.

Research Funding

• Civil Aviation Authority of Singapore
  Airfield and Airspace Management
  Total Award: SGD 720,000

• SUTD Startup Research Grant
  Airport Congestion Mitigation
  Total Award: SGD 100,000

International Collaborations

• University of Bergamo (Italy)
  Collaboration with Sebastian Birolini on predictive and prescriptive analytics for airport capacity management.