Can We Predict Steering Control Performance from a 2D Shape Detection Task?
Author(s) -
Bobby Nguyen,
Yan Zhuo,
Ruiqing Ni
Publication year - 2013
Language(s) - English
Resource type - Conference proceedings
DOI - 10.17077/drivingassessment.1486
Subject(s) - visibility , contrast (vision) , task (project management) , perception , computer science , computer vision , optical flow , artificial intelligence , control (management) , visual perception , engineering , psychology , geography , systems engineering , neuroscience , meteorology , image (mathematics)
Research has shown the importance of spatial and temporal integration of visual information in motion perception and steering control under reduced visibility conditions. The current study examined the relationship between a 2D shape detection task and a steering control task under reduced visibility conditions for younger drivers. In the 2D shape detection task, the spatial and temporal characteristics, and the contrast of the stimuli were manipulated by varying the number, the lifetime, and the contrast of the random dots. In the steering task, the visibility of the driving scene was manipulated by varying the quantity and quality of the optical flow information. The authors found that the correlation between shape detection task and steering control task under low contrast conditions depended on temporal integration. These results suggest that under reduced visibility conditions, temporal integration of visual information may play a larger role than spatial integration.
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