Airport Flight Capacity Assessment Method and System Based on Congestion Costs

By constructing a nested reward alternating update strategy between an upper-level airport time slot management agent and a lower-level airline demand response agent, the problem of difficulty in online assessment of airport rolling time slot capacity is solved, realizing real-time optimization of airport flight capacity and efficient utilization of resources.

CN122311628APending Publication Date: 2026-06-30NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Filing Date
2026-04-03
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

In existing technologies, it is difficult to achieve rapid online assessment and stable updates of airport rolling time slot capacity under conditions of multi-airline interaction, resulting in high operating costs and low resource utilization efficiency.

Method used

An upper-level Airport Time Slot Management Agent (ASPA) and a lower-level Multi-Airline Demand Response Agent (ARA) are constructed. Through a nested reward alternation update strategy, a closed-loop iteration is formed to realize the online assessment and collaborative optimization of airport flight throughput capacity.

Benefits of technology

It improved the real-time performance and resource utilization efficiency of airport congestion management, reduced operating costs, and enhanced the airport's operational resilience and flexible management capabilities at the tactical level.

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Abstract

This invention belongs to the field of airport congestion management and time slot resource allocation technology, specifically involving a method and system for assessing airport flight capacity based on congestion cost. This invention constructs an airport flight capacity assessment method based on congestion cost to achieve closed-loop linkage optimization of airport time slot capacity calculation and multi-airline demand response. Compared with existing technologies, this invention achieves rolling online updates of time slot cost signals and demand adjustments through interactive modeling of upper-layer time slot management agents and lower-layer airline response agents; it improves solution efficiency and scalability by learning multi-agent strategies in parallel under a centralized training and distributed execution framework; and it enhances the executability and stability of congestion management strategies through state interaction embedding, thereby improving airport congestion mitigation and time slot resource utilization efficiency. This provides feasible algorithmic support and application paths for real-time demand control during airport tactical operations, filling a technological gap in related fields.
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