Optic flow is used to control human walking

Abstract

How is human locomotion visually controlled? Fifty years ago, it was proposed that we steer to a goal using optic flow, the pattern of motion at the eye that specifies the direction of locomotion. However, we might also simply walk in the perceived direction of a goal. These two hypotheses normally predict the same behavior, but we tested them in an immersive virtual environment by displacing the optic flow from the direction of walking, violating the laws of optics. We found that people walked in the visual direction of a lone target, but increasingly relied on optic flow as it was added to the display. The visual control law for steering toward a goal is a linear combination of these two variables weighted by the magnitude of flow, thereby allowing humans to have robust locomotor control under varying environmental conditions.

Controlling steering and judging heading: Retinal flow, visual direction, and extraretinal information.

“…Harris and Rogers (1999) stated: "We challenge flow researchers to provide some compelling evidence for a significant role of optic flow in the control of direction of locomotion on foot" (p. 449). Warren et al(2001) would claim to have answered that "on foot," but we have reinforced this in a task more akin to steering a vehicle. The task we have presented could be considered as simple "rotation nulling," because to steer accurately observers must bring the target gates in front of them.…”

“…The ER and VD information is unaffected by the rotation, and hence there is a dissociation between the three sources of information. The manipulation differs from a virtual prism (Warren et al, 2001) in that a simple prism would not dissociate the velocity components of ER and VD from RF. 4 A Figure 10.…”

“…This tested the relative weighting that participants ascribed to RF or a strong VD cue and extends the debate of Rushton et al (1998) and Warren et al (2001) to the task of curvilinear steering.…”

A neural model of visually guided steering, obstacle avoidance, and route selection.

“…Figure 23 The STARS model is able to replicate the findings of Warren et al (2001). Since our model is unable to "crab-walk" like human subjects, we shift the direction the model's viewpoint moves by 10º, which is equivalent to shifting visual space relative to the locomotor axis with a prism.…”

“…See text for additional details The leftmost column shows a screenshot of the environment at the start of the simulation. The second column shows the experimental data obtained by Warren et al (2001), and the third column shows results generated using the model proposed in that study. The rightmost column shows simulation results obtained using the STARS model.…”