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少数驾驶员适度饮酒后安全驾驶能力不降反升和不同人对酒精作用存在个体差异的事实表明:利用血液酒精浓度(BAC)判定酒后驾车行为的技术方案存在不足。为探索新型量化参数,结合酒后状态诱发试验和模拟驾驶测试,测取12位驾驶员不同程度饮酒后的脑电(EEG)和规范化交通事故倾向指标。结果发现:随着饮酒量的增加,驾驶员左额叶区EEG的瞬时复杂度和长时周期度都增加。结合模糊熵算法构造并计算EEG特征参数。相关性分析表明:在驾驶员从未饮酒到重度饮酒的过程中,其左额叶区EEG模糊熵和规范化事故倾向指标间的平均相关系数为0.76,二者正相关。因此,根据该模糊熵变化能判断其酒后安全驾驶能力的变化。
The fact that the driver’s ability to drive safely after a moderate amount of alcohol consumption increases non-decreasingly and that there are individual differences in the role of alcohol in different persons indicates that there are deficiencies in the technical solution to determine the behavior of drink-driving by using blood alcohol concentration (BAC). In order to explore new quantitative parameters, combined with postprandial state-induced test and simulated driving test, 12 drivers were tested for EEG and standardized traffic accident tendency indicators. The results showed that with the increase of alcohol consumption, the instantaneous complexity and long-term period of driver’s EEG in the left frontal lobe increased. Combined with fuzzy entropy algorithm to construct and calculate EEG characteristic parameters. Correlation analysis showed that there was a positive correlation between the EEG fuzzy entropy and the normalized accident tendency index of the left frontal lobe in the process of never drinking alcohol to severe alcohol consumption. Therefore, according to the change of fuzzy entropy to determine the change of safe driving ability after drinking.