The EUROCONTROL SHAPE project examines how new automation affects human operators in air traffic management (ATM). This initiative has developed a series of questionnaires to evaluate how automation influences workload, situational awareness, teamwork, and trust. As automation increases in European ATM, it raises various concerns. The success of automation hinges on its compatibility with controllers’ needs. Past experiences in cockpit automation show that neglecting human factors can lead to ‘automation-assisted failures.’
Seven key issues must be addressed for effective automation implementation:
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Trust: Controllers’ reliance on automated tools depends on their trust in the system. Trust stems from factors like system reliability and transparency. Both mistrust and overtrust can hinder effective tool usage.
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Situational Awareness (SA): Changing task allocations between humans and machines can affect controllers’ SA. It is crucial to ensure that automation does not significantly compromise their awareness of the situation.
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Teamwork: New automation can alter teamwork dynamics and interactions. This includes how tasks are assigned among team members and how they share information.
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Changes in Skill Requirements: Automation may lead to skill degradation or the need for new skills. It’s essential to analyze these changes to support successful automation adoption, including identifying required training and potential skill loss.
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Recovery from System Failure: While automation can prevent certain human errors, it can also fail. In such cases, controllers must effectively diagnose and respond to these failures. Planning for safe recovery from system failures is necessary.
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Workload: While the goal of automation is often to reduce workload by transferring tasks to machines, it can introduce new cognitive demands. Ensuring that automation does not increase controllers’ workload is vital.
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Ageing: The age of controllers can influence how well automation is received. Tools must be designed to be suitable and acceptable for controllers across different age groups.
The SHAPE questionnaires facilitate the empirical assessment of new automation in ATM. Revised in 2007, these questionnaires enhance usability, improve psychometric properties, and offer better guidance for data analysis. Available questionnaires include:
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Assessing the Impact of Automation on Mental Workload (AIM)
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SHAPE Teamwork Questionnaire (STQ)
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Situational Awareness for SHAPE (SASHA)
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SHAPE Automation Trust Index (SATI)
These questionnaires are user-friendly, require minimal effort from participants, and simplify data analysis. Some questionnaires come in both short and long formats and can be used in simulations as well as operational trials.
