Indoor vehicle pass-by noise applications deal with measuring the exterior noise from a vehicle fixed on a chassis dynamometer in a large hemi-anechoic room. During a standardised acceleration test, the noise is measured with an array of microphones placed in the far-field, and the overall noise level versus vehicle position can be simulated. The indoor facility allows controlled and repeatable measurements independent of weather. For engineering purposes, pass-by contribution analysis can be included in the test leading to information about the pass-by noise contribution from major noise sources.This work presents a novel application of blind source separation to vehicle measurements from an indoor pass-by measurement campaign. In contrast to the classical transfer path approach using point sources for modelling vehicle noise sources and combining an operational measurement with transfer functions, the blind approach does not consider a specific noise source model. It only assumes that the noise is produces by a set of independent noise sources using only a single operational measurement for a given vehicle condition as input. Near-field microphone measurements are blindly separated into independent components and further correlated with the signals measured at the far-field indoor pass-by microphones to get the time-domain contributions. Finally, we apply the indoor simulated pass-by algorithm to produce noise contribution levels as a function of vehicle position.We discuss the specified application of blind source separation to vehicle measurements for different operating conditions from a real indoor pass-by test. Separation of tyre and engine related noise at tyre near-field microphones is verified. Furthermore, the tyre pass-by noise contribution is extracted from the overall vehicle measurement.