Participants used a position control system to track the center of a simulated winding roadway with preview that ranged from 0.3 to 1.0 s. Participants’ spatial distributions of attention were measured by perturbing the roadway with different frequency sinusoids at different roadway positions and then measuring the degree to which those frequencies were present in their tracking movements. Consistent with Miller's optimal control theory analysis of tracking with preview, participants exhibited a continuous range of attention, and it lengthened with the amount of displayed preview. When the displayed preview disappeared for 5 s, the time to reach a steady-state level of tracking error based only on feedback control was measured. More displayed preview was strongly correlated with longer times to regress to feedback control. One interpretation of this finding is that when preview is withdrawn, visual sensory memory of the previewed roadway can be used for a fraction of a second to prolong the period of feedforward control. Attention can be shifted to relevant positions of the sensory memory image to anticipate the roadway curvature. However, the quality and usefulness of sensory memory gradually diminishes until the participant can only perform feedback control. When preview was restored, the time to reach steady-state feedforward control was correlated with the range of attention. These findings characterize some of the dynamic aspects of attention when drivers are briefly interrupted from viewing the upcoming roadway. This measurement technique may be useful for characterizing spatially distributed attention in other active control contexts.

In this paper, we present a novel design concept for a robot arm link with variable stiffness. Variable stiffness links are intended to grant a robot the safety benefits of compliance and the performance benefits of stiffness. Our compact design actively modulates stiffness via parallel, rotating beams actuated by simple servomotors. It achieves a lateral stiffness ratio greater than ten with a minimum stiffness under 0.2 N/mm. Our novel design offers many benefits over existing variable stiffness link solutions in its compactness, simplicity, and speed of actuation. One challenge of this research lies in the mechanics modeling of variable stiffness. Here we propose a comprehensive mechanics model that considers mechanical compliances due to deflections of parallel guided beams, column buckling, and bearing at the beam roots. By comparing with experimental testing data, we show that our analytical model accurately predicts the lateral stiffness of the robotic link. This model can be used as a design tool in future iterations, including for scaling the design.

The spatiotemporal distribution of drivers' attention to preview was inferred from their steering movements while tracking a winding roadway in a laboratory setting. For most subjects, the average driving attentional distribution over six daily sessions was relatively stable and generalized across different control devices. However, there was considerable day-to-day variability in the attentional distributions. This variability was modeled as a strong interaction between two dynamic processes, the attentional emphasis of selected regions and inhibition of surrounding regions. The model combines a novel application of a reaction-diffusion model of biological pattern formation with an optimal control model of attention to preview. The combined model treats attentional dynamics as an example of the biological spacing of a limited cognitive resource, which is also shaped by the demands of action.