Aimed at problem that driver's visual search mode evaluated by single eye movement parameter is one-sided and has relative large errors, an evaluation method was presented by using fuzzy theory. In this method, five characterized visual parameters, including driver's fixation duration, horizontal visual angle, vertical visual angle, saccade amplitude and saccade velocity were synthesized. By performing field tests in real road traffic environment, recording driver's eye movement data while driving, and building fuzzy similar matrices and fuzzy equivalent matrices, the optimal threshold value was determined according to the clustering sample driver's driving mileage, and the sample driver's visual search modes were classified into four categories. Taking visual search mode feature of each driver category as criteria, the other driver's visual search modes were identified and evaluated by closeness optimization principle. The result shows that the evaluation method is effective and reliable.
Key words
traffic engineering /
driver /
fuzzy theory /
visual search mode /
evaluation method /
clustering analysis
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