Impact of Traffic-Following on Order of Autonomous Airspace Operations
arxiv(2024)
摘要
In this paper, we investigate the dynamic emergence of traffic order in a
distributed multi-agent system, aiming to minimize inefficiencies that stem
from unnecessary structural impositions. We introduce a methodology for
developing a dynamically-updating traffic pattern map of the airspace by
leveraging information about the consistency and frequency of flow directions
used by current as well as preceding traffic. Informed by this map, an agent
can discern the degree to which it is advantageous to follow traffic by trading
off utilities such as time and order. We show that for the traffic levels
studied, for low degrees of traffic-following behavior, there is minimal
penalty in terms of aircraft travel times while improving the overall
orderliness of the airspace. On the other hand, heightened traffic-following
behavior may result in increased aircraft travel times, while marginally
reducing the overall entropy of the airspace. Ultimately, the methods and
metrics presented in this paper can be used to optimally and dynamically adjust
an agent's traffic-following behavior based on these trade-offs.
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