The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as vehicle excitation data since most of the excitation exerted on a vehicle as it traverses terrain is provided by the terrain topology. It is currently not efficient to obtain accurate terrain profile data of sufficient length to simulate the vehicle being driven over long distances. Hence, durability and ride quality evaluations of a vehicle depend mostly on data collected from physical tests. Such tests are both time consuming and expensive, and can only be performed near the end of a vehicle's design cycle.This paper covers the development of a methodology to synthesize terrain profile data based on the statistical analysis of physically measured terrain profile data. The synthesized terrain profiles generated can be of any desired length, are expected to possess statistical properties similar to the seminal measured data, and will provide vehicle designers with an accurately modeled virtual road on which to base simulations of vehicle durability and ride quality.The synthetic terrain is generated by using an autoregressive (AR) model to represent measured road profile data points as a linear combination of the preceding data points in that profile, and a residual function. The residual process is considered to be a realization of a stochastic process. The measured profile forms the basis on which the synthetic profile is generated, leading to a terrain model having both stochastic and deterministic properties. The measured and synthesized terrain profiles are analyzed to obtain metrics of their statistical properties relevant to terrain profile analysis (e.g. rainflow count, international roughness index etc.). These metrics are then used as a means to optimize the parameters of the autoregressive model such that the statistical conformity of the synthesized terrain to the measured terrain is maximized. The performance of the model in this respect is also evaluated through statistical tests.