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探讨了经济性与社会性奖惩机制在不同风险水平下对航空决策行为的影响，并通过分层漂移扩散模型分析了潜在的认知机制。采用2(奖惩机制：经济性、社会性)×4(风险水平：安全、中等风险、高风险、极高风险)的两因素试验设计，招募32名拥有商业航空执照的飞行员完成简化着陆任务，记录其着陆率、反应时及分层漂移扩散模型参数。结果表明：(1)社会性奖惩机制在中等风险和高风险情境下显著降低了飞行员的着陆率，并在高风险和极高风险情境中显著缩短了决策反应时；(2)漂移率分析显示，社会性奖惩机制在高风险和极高风险情境下显著提高了信息积累速率，加快了决策过程；(3)起始点分析显示，社会性奖惩在安全情境中更偏向着陆选择，而在极高风险情境中更偏向复飞选择。研究结果表明，社会性奖惩机制在不确定性情境下更能有效引导飞行员做出更安全的决策，为优化航空领域的奖惩机制设计提供了理论依据。
Abstract：Pilot decision-making during high-risk flight phases is crucial for aviation safety. While previous studies have indicated that decision-making is influenced by both economic and social reward-punishment mechanisms, their differential effects under varying levels of risk remain unclear. This study aims to investigate the impact of economic and social reward-punishment mechanisms on pilots' decision-making across different risk levels, as well as to explore the underlying cognitive processes utilizing the Hierarchical Drift Diffusion Model(HDDM). A 2(reward-punishment mechanism: economic, social) × 4(risk level: safe, moderate risk, high risk, extremely high risk) factorial experimental design was conducted with 32 licensed commercial pilots(flight hours=230-260). Participants completed a simplified landing task in which they had to decide whether to continue or terminate the landing based on four risk levels(safe, moderate risk, high risk, and extremely high risk) under both economic and social reward-punishment mechanisms. Landing rates, response times, and HDDM parameters were recorded for each participant. Statistical analyses included repeated measures ANOVA, K-means clustering, and HDDM modeling using Markov-chain Monte Carlo sampling(5 000 samples, ■< 1.1, effective sample size > 400). The results indicated that:(1) The social reward-punishment mechanism significantly decreased pilots' landing rates under moderate(p<0.001) and high-risk conditions(p<0.001), and it shortened decision response times under high-risk(p=0.029) and extremely high-risk conditions(p<0.001) compared to the economic reward-punishment mechanism.(2) Drift rate analysis indicated that the social reward-punishment mechanism enhanced information accumulation rates under high-risk and extremely high-risk conditions, thereby accelerating decision-making.(3) Starting point analysis revealed that pilots operating under the social reward-punishment mechanism displayed a preference for landing in safe conditions but were more inclined to opt for go-around decisions in extremely high-risk situations. These findings suggest that the social reward-punishment mechanism can effectively steer pilots towards safer decision-making, particularly in uncertain and high-risk situations. The HDDM analysis offers deeper insights into cognitive mechanisms, including information accumulation rates and shifts in decision preferences. This study provides theoretical implications for optimizing reward-punishment systems in aviation, ultimately aimed at enhancing flight safety.
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基本信息:
DOI：10.13637/j.issn.1009-6094.2025.0142
中图分类号:F560;V328
引用信息:
[1]彭姓,王翔,仲家瑞,等.奖惩机制在不同风险水平下对航空决策的影响[J].安全与环境学报,2026,26(01):21-30.DOI:10.13637/j.issn.1009-6094.2025.0142.
基金信息:
国家自然科学基金项目(U2133209); 教育部人文社会科学研究青年基金项目(2IYIC190012); 民航飞行技术与飞行安全重点实验室项目(FZ2021ZZ02)
2025-07-30
2025-07-30
2025-07-30