Supporting Operator Complexity Management in Supervisory Control Systems

航空、过程控制和核电行业的人工操作员在维护这些企业的安全运行方面发挥着关键作用，对世界贸易和商业做出了重大贡献。然而，当犯错误时，后果可能是代价高昂的，而且往往是悲剧性的。错误的一个关键来源可能是过于复杂。经验丰富的运营商制定了管理和降低复杂性的强大战略和技术。然而，新技术的引入可能会破坏或扰乱这些战略。这项研究的主要目标是了解如何有效地支持运营商复杂性管理策略，同时为系统运营引入灵活性和提高效率。 拟议的研究计划将调查空中交通管制领域内的复杂性管理，并将研究结果外推到其他领域。将利用对当前系统操作的观察和检查操作员任务环境的具体变化的部分任务实验的结果来生成信息和任务设计要求，并开发和评估原型决策支持工具，以维护安全和更有效的操作。将使用其他监督控制领域内的其他案例研究来进一步了解关键的研究问题。

Human operators in the aviation, process control and nuclear power industries play key roles in maintaining the safe operation of these enterprises with significant contributions to world trade and commerce. However, when mistakes are made, the consequences can be costly and often tragic. A key source of mistakes can be excessive complexity. Experienced operators develop powerful strategies and techniques for managing and reducing complexity. However, the introduction of new technologies can undermine or disrupt those strategies. The primary objective of this research is to understand how to effectively support operator complexity management strategies while introducing flexibility and increased efficiency to system operations. The proposed research program will investigate complexity management within the Air Traffic Control domain and extrapolate findings to other domains. Observations of current system operations and the results of part-task experiments examining specific changes to the operator task environment will be used to generate information and task design requirements and develop and evaluate prototype decision support tools preserving safe and more efficient operations. Additional case studies within other supervisory control domains will be used to further understand the key research issues.