Adaptive Traffic-Following Scheme for Orderly Distributed Control of Multi-Vehicle Systems

--We present an adaptive control scheme to enable the emergence of order within distributed, autonomous multi-agent systems. Past studies showed that under high-density conditions, order generated from traffic-following behavior reduces travel times, while under low densities, choosing direct paths is more beneficial. In this paper, we leveraged those findings to allow aircraft to independently and dynamically adjust their degree of traffic-following behavior based on the current state of the airspace. This enables aircraft to follow other traffic only when beneficial. Quantitative analyses revealed that dynamic traffic-following behavior results in lower aircraft travel times at the cost of minimal levels of additional disorder to the airspace. The sensitivity of these benefits to temporal and spatial horizons was also investigated. Overall, this work highlights the benefits, and potential necessity, of incorporating self-organizing behavior in making distributed, autonomous multi-agent systems scalable. Autonomous vehicle operations are expected to increase in the airspace over the coming decades. Initially, applications will include non-passenger operations, such as fire fighting or cargo delivery using uncrewed aerial vehicles of different sizes. Eventually, the scope will expand to passenger-carrying vehicles for urban or regional air mobility. These vehicles are expected to interact and integrate with other traffic within the same airspace. For scalability, this airspace of the future will be a collective system of autonomous vehicles, where each vehicle makes increasingly independent decisions.