July 2013
Volume 13, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Visually guided overtaking behavior understood in relation to the maximal acceleration of vehicle: an affordance-based approach
Author Affiliations
  • Numa Basilio
    Aix-Marseille University, CNRS, ISM UMR 7287, France
  • Antoine H.P. Morice
    Aix-Marseille University, CNRS, ISM UMR 7287, France
  • Geoffrey Marti
    Aix-Marseille University, CNRS, ISM UMR 7287, France
  • Gilles Montagne
    Aix-Marseille University, CNRS, ISM UMR 7287, France
Journal of Vision July 2013, Vol.13, 946. doi:10.1167/13.9.946
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      Numa Basilio, Antoine H.P. Morice, Geoffrey Marti, Gilles Montagne; Visually guided overtaking behavior understood in relation to the maximal acceleration of vehicle: an affordance-based approach. Journal of Vision 2013;13(9):946. doi: 10.1167/13.9.946.

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

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Abstract

Fajen [1] suggests that the affordance-based approach can explain how successful goal-directed behaviors are selected and regulated in accordance with our own action capabilities. We test such a hypothesis in a virtual driving simulator by investigating the influence of action boundaries of driven cars while overtaking. A previous experiment [2] reports that drivers use an informational variable based on the Minimum Satisfying Velocity (MSV) related to the maximum Velocity of the driven car (VMAX), in order to perform safe overtaking. However, the perception of overtaking possibility through the MSV/VMAX ratio cannot account for the influence of more relevant kinematics features of automobiles such as acceleration. We therefore challenged our previous proposition and assumed in this present experiment that a new perceptual variable, defined as the Minimum Satisfying Acceleration (MSA) divided by the maximum Acceleration of the driven vehicle (AMAX), would accurately inform drivers about overtaking possibilities. Two groups of drivers were asked to perform overtaking maneuvers, if deemed possible, by driving virtual cars with one of two AMAX values (2 m/s² or 3.5 m/s²). Twenty five overtaking situations were set-up by combining 5 MSA and 5 MSV values. Firstly, our results showed that overtaking frequency significantly decreases when increasing the MSA and MSV values and becomes null for all groups when extrinsic task constraints exceed group action capabilities for both groups of participants. Secondly, we were able to show the significant differences between the groups in an extrinsic scale (i.e., function of MSA and MSV) disappear when an intrinsic scale is applied (i.e., function of MSA/AMAX and MSV/VMAX). These results are identical to our previous findings [3], [4] and confirm that MSA/AMAX is a correct ratio to account for visually guided overtaking behavior. Future analyses will be designed to investigate how MSA/AMAX affordance can account for the regulation of overtaking.

Meeting abstract presented at VSS 2013

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