as a basis for evaluating vehicle operational properties and their potential environmental implications. Driving velocity processes were modelled as sets of empirical process representations-velocity courses-recorded under four characteristic traffic conditions: urban driving with congestion, urban driving without congestion, rural driving and fast-road driving (on highways and expressways). Zero-dimensional statistical characteristics were determined for each representation and sets with similar mean values, maximum values and coefficients of variation were selected as stochastic models of the underlying processes. The low non-repeatability of these characteristics confirms the statistical stability of the representations.

The analyses were conducted in the domain of time, process value and frequency, including probability density estimation and power spectral density

The power spectral density (PSD) is a function that describes the distribution of the power of a signal or stochastic process across individual frequencies. It is defined as the Fourier transform of the autocorrelation function and makes it possible to identify which frequency components dominate the signal and how intense its temporal variations are.