In the last decade, many papers focused on the study of the variability of passenger journey time in multimodal transport networks in cities on an aggregated level. Unfortunately, among this considerable body of research, only few papers account for passenger underlying walking factors, named walking speed and walking distance, in mass transit stations on disaggregated level. Our recent research tried to overcome this drawback by modelling a uniform-distributed walking speed in a general stochastic model along a mass transit line. To optimize our previous model, a new model M1 with normal-distributed walking speed is confronted with the previous models M2 with a uniform distribution and M0 with fixed value of walking speed. A global comparison approach is proposed to compare those models from numerical analyses, modelling and optimization framework to real case study. Numerical analyses of the analytical formulae hold for detailed comparisons for each part of the stochastic model. The closed-form formula of the general function of M1 in Maximum Likelihood Estimation is reduced to 5 pieces. On the contrary, M2 involves 17 different pieces. The real case study of the busiest express rail transit line RER A in Parisian region is applied based on the AFC and AVL data with standard statistical features analyses of the basic distributions, yielding a better model. This model will be integrated in a new passenger mobility information model based on AFC and AVL data.
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