Improving Risk Assessment in Aviation: Information Seeking, Planning, and Judgment

以往的风险评估研究主要集中在静态环境中，决策者通常得到充分的信息来判断所涉及的风险水平。根据该奖项进行的研究将扩展以前的研究，以研究飞行前和飞行中计划期间由持牌飞行员进行的风险评估，其中飞行员必须不断寻找和整合多种信息来源（如天气，空中交通和地形），以评估高度动态环境中的风险。具体而言，该项目将研究涉及飞行员风险评估的三大类活动：（1）信息寻求，（2）飞行计划期间的信息整合，以及（3）不同飞行路径的风险评估。详细的行为数据将从高保真飞行模拟器中收集。数据将基于假设两种不同决策系统的理论框架进行分析：一种是对行动施加明确的自上而下指导的理性系统，另一种是能够将外部环境线索与过去的奖惩历史联系起来的经验系统。这一理论框架将有助于理解背景知识和技能如何与动态环境中的不同信息寻求行为模式和风险评估相关。这项研究应产生新的知识，对改进动态环境中风险评估的培训方法具有实际意义。

Previous research on risk assessment has largely focused on static environments in which the decision maker is usually given full information to judge the level of risks involved. Research conducted under this award will extend previous research to study risk assessments by licensed pilots during pre-flight and in-flight planning, in which the pilots have to continuously look for and integrate multiple sources of information (such as weather, air traffic, and terrains) to assess risks in a highly dynamic environment. Specifically, the project will study three major classes of activities involved in pilot risk assessments: (1) information-seeking, (2) information integration during flight planning, and (3) risk assessments of different flight paths. Detailed behavioral data will be collected from a high-fidelity flight simulator. The data will be analyzed based on the theoretical framework that assumes two distinct systems of decision making: A rational system that exerts explicit top-down guidance on actions, and an experiential system that is capable of associating external environmental cues to past history of rewards and punishments. This theoretical framework will help to understand how background knowledge and skills are related to different patterns of information-seeking behavior and risk assessments in dynamic environments. The research should produce new knowledge with practical implications for training methods that improve risk assessments in dynamic environments.