Emotional and Affective Signals in Air Traffic Control Decision-Making: Toward an Integrative Framework for Proactive Conflict Detection

Abstract

Paper Description This conceptual paper examines the potential role of emotional and affective states as early warning signals in air traffic control (ATC) decision-making. Air Traffic Control Officers (ATCOs) work in highly safety-critical environments where continuous monitoring, rapid decision-making, and accurate conflict detection are essential. While previous human factors research has primarily emphasized cognitive variables such as mental workload, stress, situation awareness, experience, and decision accuracy, comparatively little attention has been given to whether emotional states and subjective affective signals can provide useful information about emerging conflicts before they become objectively detectable. Drawing on evidence from affective neuroscience, cognitive psychology, and ATC human factors research, the paper proposes an integrative framework in which emotional and physiological signals are considered active components of the ATC decision-making process rather than sources of cognitive interference or performance degradation. The framework incorporates several theoretical perspectives, including somatic marker theory, conflict monitoring models, and recognition-primed decision-making. It further considers the potential influence of cortisol-mediated stress responses, confidence calibration, emotional regulation, age-related changes in neuroplasticity, automation, workload, and environmental conditions. The central argument is that effective conflict detection may depend on a dynamic interaction between deliberate analytical reasoning and intuitive affective processing. In this framework, experienced controllers may use subtle emotional or physiological cues as implicit indicators of emerging risk, particularly under conditions of uncertainty, time pressure, or high workload. Individual differences in emotional regulation, confidence, experience, and workload are proposed as important moderators of this process. Rather than treating emotions exclusively as sources of distraction or performance impairment, this paper proposes a paradigm shift toward viewing affective states as potentially informative early warning signals within the ATC decision-making loop. To evaluate this proposition empirically, the paper outlines testable hypotheses and suggests combining physiological measures, self-report instruments, behavioral performance indicators, and experimental manipulation. The proposed framework has potential implications for ATC controller training, human–automation interaction, interface design, workload assessment, and safety management systems.