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Title: Game-Theoretic Decision-Making and Payoff Design for UAV Collision Avoidance in a Three-Dimensional Airspace
Safety and efficiency are primary goals of air traffic management. With the integration of unmanned aerial vehicles (UAVs) into the airspace, UAV traffic management (UTM) has attracted significant interest in the research community to maintain the capacity of three-dimensional (3D) airspace, provide information, and avoid collisions. We propose a new decision-making architecture for UAVs to avoid collision by formulating the problem into a multi-agent game in a 3D airspace. In the proposed game-theoretic approach, the Ego UAV plays a repeated two-player normal-form game, and the payoff functions are designed to capture both the safety and efficiency of feasible actions. An optimal decision in the form of Nash equilibrium (NE) is obtained. Simulation studies are conducted to demonstrate the performance of the proposed game-theoretic collision avoidance approach in several representative multi-UAV scenarios.  more » « less
Award ID(s):
2235160
PAR ID:
10586517
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
World Scientific Publishing
Date Published:
Journal Name:
Unmanned Systems
Volume:
12
Issue:
03
ISSN:
2301-3850
Page Range / eLocation ID:
499 to 509
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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