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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2009  >  9(2): 105-109
LIU Hao-xue, ZHAO Wei-hua, LIU Kai-zheng, ZHANG Juan, ZHOU Jing. Cognitive regulation of space distance about drivers to genial tone obstacles in daytime dynamic environment[J]. Journal of Traffic and Transportation Engineering, 2009, 9(2): 105-109. doi: 10.19818/j.cnki.1671-1637.2009.02.019
Citation: LIU Hao-xue, ZHAO Wei-hua, LIU Kai-zheng, ZHANG Juan, ZHOU Jing. Cognitive regulation of space distance about drivers to genial tone obstacles in daytime dynamic environment[J]. Journal of Traffic and Transportation Engineering, 2009, 9(2): 105-109. doi: 10.19818/j.cnki.1671-1637.2009.02.019
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Cognitive regulation of space distance about drivers to genial tone obstacles in daytime dynamic environment

doi: 10.19818/j.cnki.1671-1637.2009.02.019

  • School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China

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  • Author Bio:

    LIU Hao-xue(1956-), male, professor, PhD, +86-29-82334457, liuhx@chd.edu.cn

  • Received Date: 2008-10-26
  • Publish Date: 2009-04-25
    Abstract
  • The cognition data of absolute distances and relative distances for 32 drivers who were selected randomly, were obtained and disposed through statistic and regress analysis. The quantitative variation laws about cognitive distances to genial color tone obstacles were studied in ground dynamic environment. Six cognitive mathematical models about absolute and relative space distances under the conditions of three different distances that are 25, 75, 125 m were established. Analysis result shows drivers' cognition accuracy for absolute distance in depth direction decreases with the increase of actual distance, and the accuracy of relative distance cognition is higher than that of absolute distance cognition. With the increase of vehicle velocity, the accuracy of distance cognition declines continuously, and there is a negative exponential relationship between cognitive distance and vehicle velocity. The minimum correlative coefficient of the models is 0.941, so they are feasible.

     

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