To improve sound quality in cars, a preference map was created on the basis of several acoustic parameters relevant to auditory perception. A multidimensional scaling technique (CLASCAL) was used to reveal common perceptual dimensions shared by sets of car sounds, perceptual features specific to each sound, and the different subject classes among listeners. The listeners' task was to judge the degree of dissimilarity of all pairs of car sounds on a continuous scale. The analysis gives a perceptual spatial representation of the sounds. From this analysis, acoustic and auditory modelling analyses indicated that a number of stimulus parameters were strongly correlated with different perceptual dimensions and, where possible, with the specific features. A further experiment investigated the probability of one sound being preferred to another. An analysis of the data allowed a projection of the structure of listeners' preferences onto the physical parameter space underlying the previously determined multidimensional perceptual space. In many cases, it was found that the physical parameters having the most effect on the listeners' preferences were dependent on the set of stimuli being compared.