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