为综合考虑三维道路线形对运行速度的影响，在三维点云环境下，文中结合驾 驶员动视野进行运行速度预测研究。首先，利用点云数据标定道路及两侧地形，建立三 维点云道路环境; 其次，通过点云坐标转换与投影，建立以驾驶员视点为中心的视平面 模型，获得驾驶员静视野图像; 然后，根据空间几何原理与动视野参数计算投影椭圆方 程，获得驾驶员动视野图像; 最后，采用动视野路占比作为运行速度的研究指标，并依 据车辆动力性能与阈值控制建立运行速度预测模型。以宁杭高速公路东庐山段为例对文 中提出的预测模型进行实例验证，结果表明: 运行速度模型预测值与实测值对于小客车 和大货车的相对误差平均值分别为 2. 726% 和 9. 023% ; 由大货车预测结果可知，该段 属线形不良路段，与实测结果对线形的判断一致，所提出的预测模型可有效解决现有模 型在高速公路划分路段单元内运行速度无法准确预测的问题。

To comprehensively consider the influence of the three-dimensional road alignment on the operating speed，the research on the operating speed prediction in the three-dimensional point cloud environment was carried out based on the driver's dynamic visual field． Firstly，the point cloud data was used to calibrate the road and the terrain on both sides，and the three-dimensional point cloud road environment was established． Secondly，through the transformation and projection of point cloud coordinates，the view plane model with the driver's viewpoint as the center was constructed to obtain the driver's static visual field image． Thirdly，according to the principle of space geometry and the parameters of dynamic visual field，the projection ellipse equation was calculated and the driver's dynamic visual field image was obtained． Finally，the road-to-dynamic-visual-field-area-ratio was used as the research index of operating speed，and the operating speed prediction model was established by the vehicle dynamic performances and threshold control． The prediction model was testified by the example of dong-lu-mountain section of Ningxia-Hangzhou freeway． The results show that the average relative error between the predicted values and the measured values is 2. 726% for passenger cars and 9. 023% for trucks． The prediction result of trucks indicates that this section is a bad alignment section and the result is consistent with the measurement result． Therefore，the proposed prediction model can effectively solve the problem that the existing model cannot accurately predict the operating speed inside the section division unit of freeway