Understanding how humans control unstable systems is central to many research problems, with applications ranging from quiet standing to aircraft landing. Much evidence appears in favor of event-driven control hypothesis: human operators are passive by default and only start actively controling the system when the discrepancy between the current and desired system states becomes in some sense large. The present paper argues that the control triggering mechanism in humans is intrinsically stochastic. We propose a model which captures the stochastic threshold mechanism and show that it matches the experimental data on human balancing of virtual overdamped stick. Our results suggest that the stochasticity of the threshold mechanism is a fundamental property and may play an important role in the dynamics of human-controlled systems.
Arkady Zgonnikov, Ihor Lubashevsky, Shigeru Kanemoto, Toru Miyazawa, Takashi Suzuki