Intercepting a moving target: On-line or model-based control?

Abstract

When walking to intercept a moving target, people take an interception path that appears to anticipate the target's trajectory. According to the constant bearing strategy, the observer holds the bearing direction of the target constant based on current visual information, consistent with on-line control. Alternatively, the interception path might be based on an internal model of the target's motion, known as model-based control. To investigate these two accounts, participants walked to intercept a moving target in a virtual environment. We degraded the target's visibility by blurring the target to varying degrees in the midst of a trial, in order to influence its perceived speed and position. Reduced levels of visibility progressively impaired interception accuracy and precision; total occlusion impaired performance most and yielded nonadaptive heading adjustments. Thus, performance strongly depended on current visual information and deteriorated qualitatively when it was withdrawn. The results imply that locomotor interception is normally guided by current information rather than an internal model of target motion, consistent with on-line control.

Figure 1

Definition of variables for interception of a moving target: heading direction (ϕ), bearing direction of the moving target (ψ_m), distance of the moving target (d_m), and target-heading angle (β = ϕ – ψ_m).

Figure 2

The target visibility conditions, as viewed from a distance of 3 m.

Figure 3

A top-down view of the experimental scenario. The green target appears, moves at a constant speed in front of a gray backdrop, and passes behind a virtual occluder (dashed line). The participant's path is indicated by the blue curve, and the red dot indicates their position when the target moves behind the occluder and is blurred; note that steering adjustments continue after the blur point.

Figure 4

Four predictions about constant and variable interception error due to increasingly degraded target visibility: on-line control hypothesis (green), high-fidelity internal model (red), medium- or low-fidelity internal model (black), and continuously updated internal model (blue).

Figure 5

Sample interception paths from one participant, from no-blur (black traces) and occlusion (red traces) conditions, for target speeds of (a) 0.6 m/s and (b) 1.0 m/s. Black circles represent the target's final position in the no-blur condition, and red circles the same in the occlusion condition. Green circles and lines represent the target's starting position and path. Asterisks on participant paths indicate the blur point when the target went behind the occluder.

Figure 6

(a) Constant error and (b) variable error of interception in each experimental condition. Error bars represent the SE.

Figure 7

(a) Mean interception point (final x position) and (b) mean walking speed after the blur point in each experimental condition. Error bars represent the SE.

Figure 8

Turning rate before blur point (a) and after blur point (b). Positive values represent turning in the target movement direction. Error bars represent the SE.