We propose a novel approach to the prediction of vehicle driving comfo
rt that allows the comfort issue to be integrated into the design proc
ess. Whereas current practice relies on building prototype driving con
figurations and asking a number of subjects to assess comfort, our app
roach will enable the design engineer to obtain predicted comfort rati
ngs on the basis of readily available design parameters, thus avoiding
the expensive and time-consuming step of building a prototype for eve
ry proposed design. We describe our approach, which focuses on the con
tribution to comfort from the design parameters of the entire driving
configuration, and the results of using a neural network to construct
a relationship between these parameters and our empirical findings on
subject comfort.