An Empirical Human Controller Model for Preview Tracking Tasks

Abstract

Real-life tracking tasks often show preview information to the human controller about the future track to follow. The effect of preview on manual control behavior is still relatively unknown. This paper proposes a generic operator model for preview tracking, empirically derived from experimental measurements. Conditions included pursuit tracking, i.e., without preview information, and tracking with 1 s of preview. Controlled element dynamics varied between gain, single integrator, and double integrator. The model is derived in the frequency domain, after application of a black-box system identification method based on Fourier coefficients. Parameter estimates are obtained to assess the validity of the model in both the time domain and frequency domain. Measured behavior in all evaluated conditions can be captured with the commonly used quasi-linear operator model for compensatory tracking, extended with two viewpoints of the previewed target. The derived model provides new insights into how human operators use preview information in tracking tasks.

Effects of Preview Time in Manual Tracking Tasks

“…In SI tasks no lead equalization is required and (2) reduces to K e ⋆ 1 . The HC's physical limitations are also included in this inner loop: τ v is the response time delay and H nms ( jω) represents the neuromuscular activation dynamics [23], modeled here as a second-order mass-spring-damper system [19],…”

“…Task characteristics (or variables) such as the Controlled Element (CE) dynamics and target trajectory bandwidth also evoke HC behavior adaptations [12], [13], and influence the effects of preview, including the critical time [5], [14]. Attempts to quantify the effects of preview time through control-theoretic modeling of driver steering [1], [15]- [18] and manual tracking [2], [3], [5], [19] account for HCs' use of preview in fundamentally different ways. We recently proposed a new quasi-linear model for preview tracking tasks [19], which captures measured HC multiloop control dynamics in tracking tasks with 0 s (pursuit) and 1 s of preview.…”

“…Attempts to quantify the effects of preview time through control-theoretic modeling of driver steering [1], [15]- [18] and manual tracking [2], [3], [5], [19] account for HCs' use of preview in fundamentally different ways. We recently proposed a new quasi-linear model for preview tracking tasks [19], which captures measured HC multiloop control dynamics in tracking tasks with 0 s (pursuit) and 1 s of preview. Preliminary experimental results suggest that this model can also capture HC adaptation to preview time [7], but this was only shown for rate control tasks with preview times between 0 and 1 s. The model's physically interpretable parameters can be directly estimated from experimental data using system identification, yielding novel quantitative insights into how HCs use preview.…”

“…We will first use the quasi-linear preview model from [19] to theoretically predict the effects of preview time offline, by finding the model parameters (i.e., the HC's behavior) that minimize the tracking error in closed-loop model simulations. Second, we verify these predictions with measurements from a human-in-the-loop experiment, in which eight subjects performed the same target-tracking and disturbance-rejection task, with eight different preview times between 0 and 2 s (well above reported critical preview times [3]- [6], [8]).…”

“…This paper is structured as follows. First, Section II introduces the considered preview tracking task and the preview control model from [19]. Predictions of the effects of preview time are presented in Section III, followed by the experimental method and the applied identification techniques in Section IV.…”