In the process of research and development of automotive products, the man-machine layout design of cab comfort has become the focus of development. At present, to judge whet that man-machine arrangement of the cab of the commercial vehicle meets the comfort requirement, a sample vehicle is usually manufacture first, Evaluated by professionals, this development process is not only cumbersome, high error rate and low efficiency, but also consumes huge human and financial resources. In this paper, the man-machine bench test of commercial vehicle is designed and carried out. The corresponding comfort evaluation data of each percentile driver under different man-machine arrangements are collected.Secondly, a RBF neural network model is built to predict the subjective evaluation of man-machine layout. The training set and test set of the model use the data from the bench test, and the accuracy of the model is evaluated by objective indicators. Finally, the secondary development of the commonly used design software CATIA is carried out, and the program is written to automatically read the size information of the three-dimensional model. One key evaluation is realized by embedding RBF neural network. The example shows that the software of RBF neural network and CATIA secondary development can greatly improve the efficiency of designers.