Segmentation of road vehicle vibration (RVV) signals can occur by the need to analyse or synthesise vibrations obtained in passenger cars or on the stowage of vans, trucks. A general and widely used measure to quantify RVV signals is its description via power spectral density (PSD). From a given PSD a Gaussian signal can be generated in a shaker testing laboratory. However, actual RVVs tend to have a non-Gaussian and nonstationary nature, which can be modelled as a composition of different segments, each with a different length and RMS content. For simulation purposes of nonstationary vibration signals, different approaches have been introduced yet each with its unique signal segmentation approaches. The current paper proposes a signal segmentation method implemented in the time-frequency domain in order to find segments within an RVV signal, where each segment has similarity in-between and is dissimilar to neighbouring segments. For this purpose, multiple comparison tests had been utilised between the Short-time Fourier transforms (STFT) applied on given fractions of an RVV. Different countermeasures had been applied against the Type I. error inflation.