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为研究换道决策阶段驾驶人对后方车辆的速度感知特征,以小型乘用车为平台,利用毫米波雷达、车载总线数据仪、音视频监测系统等搭建了试验车。招募了15名驾驶人,在某高速公路完成后方车辆速度估计试验,试验车速度分别设置为60、70、80、90km·h~(-1),最后获取了1 625组数据。采用显著性分析方法,分析了相对速度、后方车辆速度与相对距离对驾驶人速度估计行为的影响特性。利用多元线性回归理论建立了驾驶人速度估计模型,并对模型进行了检验。分析结果表明:约60%的速度估计误差绝对值不大于10km·h~(-1),且驾驶人的速度估计误差满足正态分布;驾驶人速度估计误差随两车相对速度和后方车辆速度的增大而减小,相对速度和后方车辆速度较低时,易高估后方车辆速度,相对速度和后方车辆速度较高时,易低估后方车辆速度;随两车相对距离的增大,驾驶人速度估计误差变化趋势不显著,但两车相对距离较小时,驾驶人易高估后方车辆速度;速度估计模型的平均误差为-0.56km·h~(-1),因此,估计结果可靠。
In order to study the speed perception characteristics of drivers in the lane changing decision-making stage, a small passenger car is used as a platform to build a test car using millimeter-wave radar, vehicle bus data analyzer and audio-video monitoring system. 15 drivers were enrolled and the rear vehicle speed estimation test was completed on an expressway. The speed of the test vehicle was set at 60, 70, 80 and 90 km · h -1, respectively, and finally 1 625 sets of data were obtained. The significance analysis method is used to analyze the influence of relative speed, rear vehicle speed and relative distance on driver speed estimation behavior. Based on multivariate linear regression theory, a driver speed estimation model was established and the model was tested. The analysis results show that about 60% of the absolute value of the speed estimation error is not more than 10km · h -1, and the driver’s speed estimation error satisfies the normal distribution. The driver’s speed estimation error varies with the relative speed of the two vehicles and the speed of the rear vehicle When the relative speed and lower vehicle speed is low, it is easy to overestimate the rear vehicle speed, the relative speed and the rear vehicle speed is high, it is easy to underestimate the rear vehicle speed; as the relative distance between the two vehicles increases, driving However, when the relative distance between the two vehicles is small, the driver tends to overestimate the speed of the rear vehicle. The average error of the speed estimation model is -0.56km · h -1, so the estimation result is reliable.