Incentive-driven resource trading is essential for uncrewed aerial vehicle (UAV) applications with intensive, time-sensitive computing demands. Traditional spot trading suffers from negotiation delays and high energy costs, while conventional futures trading struggles to adapt to the dynamic, uncertain UAV-edge environment. To address these challenges, we propose PAST (pilot-and-adaptive stable trading), a novel framework for edge-assisted UAV networks with spatio-temporal dynamism. PAST integrates two complementary mechanisms: PilotAO (pilot trading agreements with overbooking), a risk-aware, overbooking-enabled early-stage decision-making module that establishes long-term, mutually beneficial agreements and boosts resource utilization; and AdaptAO (adaptive trading agreements with overbooking rate update), an intelligent adaptation module that dynamically updates agreements and overbooking rates based on UAV mobility, supply-demand variations, and agreement performance. Together, these mechanisms integrate stable advance agreement construction with execution-feedback-driven adaptive renewal. Under the stated modeling assumptions, PilotAO satisfies the adopted individual-rationality and strong-stability criteria, as well as the competitive equilibrium and weak Pareto properties established for the considered trading model. Comprehensive experiments further demonstrate that, by coordinating advance planning with selective agreement renewal, PAST effectively balances stability, adaptability, and decision-making efficiency under dynamic UAV-edge conditions.

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