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针对城市道路环境中典型的应激场景,开发了虚拟仿真驾驶平台,对28名驾驶人的应激响应感知时间、判断决策时间和操作时间进行了分析,并以驾驶经验、年龄以及车速为自变量,分别建立了驾驶人感知时间、判断决策时间和操作时间预测模型。分析结果表明:驾驶人感知时间与车速呈指数函数关系,且熟练驾驶人的感知时间短于非熟练驾驶人,中青年组驾驶人的平均感知时间最短;驾驶人判断决策时间与车速之间关系不密切,但熟练驾驶人的判断决策时间长于非熟练驾驶人,青年驾驶人的平均判断决策时间最短;驾驶人操作时间与车速呈对数函数关系,且熟练驾驶人应激操作时间长于非熟练驾驶人,青年组驾驶人的平均操作时间最短。所建立的预测模型能够准确预测驾驶人的应激响应时间,总预测准确率达95%。
Aimed at the typical stress scenes in urban road environment, a virtual simulation driving platform was developed to analyze the perception of stress response time, decision-making time and operation time of 28 drivers. Based on the driving experience, age and speed Variables, respectively, the driver perception time to determine the decision-making time and operating time prediction model. The results show that the perceived time of driver is exponentially related to vehicle speed, and the perceived time of skilled driver is shorter than that of unskilled driver, and the average perceived time of driver is the shortest in young and middle-aged group. The driver judges the relationship between decision-making time and vehicle speed But the decision-making time of skilled driver is longer than that of unskilled driver, the average decision-making time of young driver is the shortest. The operating time of driver is logarithmically related to vehicle speed, and the skilled driver’s stress operation time is longer than that of unskilled driver Drivers, youth group drivers the shortest average operation time. The established prediction model can accurately predict the driver’s stress response time, the total prediction accuracy of 95%.