arXiv cs.MA· Jaehan Im, Daniel Delahaye, David Fridovich-Keil, Ufuk Topcu·· 11 小时前AI 评分24
基于博弈论的可调控去中心化协调：缓解空域扇区过载
Game-theoretic Regulated Decentralized Coordination for Airspace Sector Overload Mitigation
AI 导读
研究提出一种可调控的去中心化协议，让各空域扇区智能体基于最佳响应动态自主调整航班起飞时间以缓解自身拥堵，无需集中式联合优化。该协议引入可调的合作度因子和最小准入规则，证明在部分合作下最佳响应动态可有限时间收敛到纯 Nash 均衡。基于一个月欧洲航班数据的实验显示，即使合作程度极低也能大幅减少过载，性能接近集中式全局混合整数优化器并优于先到先服务基线，且计算量显著更低。
正文 · 原文
Abstract:Decentralized air traffic management systems offer a scalable alternative to centralized control, but often assume high levels of cooperation. In practice, such assumptions frequently break down since agents, each representing an airspace sector, may operate independently and prioritize local objectives. We address the problem of sector overload in decentralized air traffic management by proposing a regulated decentralized protocol that models self-interested behaviors based on best response dynamics. Each agent adjusts the departure times of its assigned flights to reduce its own congestion, without requiring centralized joint optimization. A tunable cooperativeness factor models the degree to which each agent accounts for overload in other sectors, while a minimal admissibility rule prevents local updates from creating new overloads. We show that this regulatory restriction is sufficient to guarantee finite-time convergence of best response dynamics to a pure Nash equilibrium under partial cooperation. In addition, we identify a sufficient condition under which an overload-free solution corresponds to a global minimizer of the potential function. Numerical experiments using one month of European flight data demonstrate that the proposed algorithm substantially reduces overload even with only minimal cooperation, achieving performance close to a centralized global mixed-integer optimizer and exceeding a centralized first-come-first-served baseline while requiring substantially less computation than centralized optimization. We further evaluate departure delay and fairness to quantify the operational cost of overload mitigation.
| Subjects: | Systems and Control (eess.SY); Computer Science and Game Theory (cs.GT); Multiagent Systems (cs.MA); Optimization and Control (math.OC) |
| Cite as: | arXiv:2511.13770 [eess.SY] |
| (or arXiv:2511.13770v3 [eess.SY] for this version) | |
| https://doi.org/10.48550/arXiv.2511.13770 arXiv-issued DOI via DataCite |
Submission history
From: Jaehan Im [view email]
[v1]
Fri, 14 Nov 2025 22:46:21 UTC (2,946 KB)
[v2]
Mon, 13 Jul 2026 21:07:57 UTC (2,945 KB)
[v3]
Wed, 4 Nov 2026 18:34:57 UTC (3,195 KB)
来源：arXiv cs.MA · arxiv.org