Cognitive Load and Trust in Automated Vehicle (AV) Handoffs: Psychological Determinants of Safe Takeover Transitions
Abstract
The rapid evolution of automated vehicles (Society of Automotive Engineers [SAE] Level 3) presents emerging safety challenges during Takeover Requests (TORs), when operational control shifts from automation to the human driver. This interdisciplinary literature review examines how cognitive load, stress, vigilance, and trust in automation jointly influence takeover preparedness, reaction time, and control performance. Drawing on recent simulator and real-world studies, the review integrates evidence through the frameworks of human-automation interaction, trust calibration, and situational awareness theory. Results indicate that elevated cognitive workload and reduced vigilance are often caused by non-driving-related tasks delay driver responses and impair lane-keeping. Excessive stress and over-trust, further impair situational awareness and motor control, whereas ideal performance occurs under moderate stimulation, reasonable trust, and sufficient TOR lead time. Evidence also shows that multi-channel TOR designs (visual and auditory) and driver-state monitoring systems improve response reliability. The review positions takeover safety as a socio-technical phenomenon shaped by human cognitive, emotional, and attentional states as much as on system design. Recommended interventions include adaptive timing of TOR, trust-regulated system transparency, and targeted training to restore situational awareness. Despite rapid technological advancement, research on the psychological demands of supervisory driving remains limited. Understanding how automation reshapes trust, stress, cognitive workload, distraction, and well-being is essential for developing human-centered strategies that support driver readiness, safety, and long-term acceptance of automated vehicle systems.
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