September 2015
Volume 15, Issue 12
Vision Sciences Society Annual Meeting Abstract  |   September 2015
Steering control using feedback from near road edges does not rely upon retinal flow.
Author Affiliations
  • Callum Mole
    School of Psychology, University of Leeds
  • Georgios Kountouriotis
    Institute for Transport Studies, University of Leeds
  • Jac Billington
    School of Psychology, University of Leeds
  • Richard Wilkie
    School of Psychology, University of Leeds
Journal of Vision September 2015, Vol.15, 415. doi:
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      Callum Mole, Georgios Kountouriotis, Jac Billington, Richard Wilkie; Steering control using feedback from near road edges does not rely upon retinal flow.. Journal of Vision 2015;15(12):415.

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      © ARVO (1962-2015); The Authors (2016-present)

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There are two potentially useful sources of information when steering along a road: retinal flow and road edges. Influential models of driving have examined the distinct roles of “near” and “far” road edge components, but it has been recently shown that flow is used even when road edges should be sufficient to control steering (Kountouriotis et al., 2013). The aim of the present study was to assess the use of flow when different road edge components were present. Participants steered along a computer simulated road on a textured ground plane, travelling at a constant speed (generating retinal flow). Flow was manipulated independent of the veridical road edges, so that use of flow would cause systematic changes to steering. Additional translation components were added to flow by moving the ground (at a speed of .75ms or 1.5ms) perpendicular to the ideal direction of travel towards the outside of the bend (predicted understeer; Fig 1A), towards the inside of the bend (predicted oversteer; See Fig 1B), or flow remained veridical (no additional translation). We also varied road edge information by displaying 7 combinations of Near road (‘N’: up to .5s ahead), Middle road (‘M’: from .5s to 1s ahead) and Far road (‘F’: from 1s to horizon) information. As predicted, steering systematically changed across the flow manipulations, however, the magnitude of the flow-induced bias varied depending on the road edge components that were visible. The presence of N seemed to decrease the influence of flow: flow bias was weakest for N+M+F (complete road), N, N+M conditions, and strongest for F conditions (see Fig 2). While these findings confirm previous observations that the visual-motor system uses flow despite the presence of veridical road edge information, it appears that flow is less influential when the immediate error correction signal is being used.

Meeting abstract presented at VSS 2015


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