This paper addresses road traffic monitoring using passive acoustic sensors. Recently, the feasibility of the joint speed and wheelbase length estimation of a road vehicle using particle filtering has been demonstrated. In essence, the direction of arrival of propagated tyre/road noises are estimated using a time delay estimation (TDE) technique between pairs of microphones placed near the road. The concatenation in time of these estimates play the role of an observation likelihood function which determine the particle weights and final convergence quality. In this paper, five classical TDE techniques are detailed and applied on a real road vehicle pass-by measurement. The obtained time series are used as likelihood functions in a particle filtering algorithm with same initial bias and parameters. The accuracy and precision for speed and wheelbase estimation are compared for each case.