The relevant parameters and their effects are analysed, in particular the sensitivity of the pressure coefficient and its rate of change on the train and pedestrian transverse size, the distance to the tracks and the pressure measurement location on the pedestrian surface.
However, the quantification of significant contributing variables on pedestrian accepted gap size is easy by MLR model as compared to the ANN technique.
In this regard, the non-linear models based on the artificial neural network (ANN), which are free from assumptions of linear models, can be easily employed for obtaining the effect of several input variables on the pedestrian accepted gap size.
Because pedestrian space includes body size, sway and distance between two pedestrians.
In addition, an estimation of the size of pedestrian flow, not only during the closures, would enhance the understanding of the proportion of transgressors among pedestrians crossing compliantly.
Accounting for differences in the size of pedestrian flow in and out of peak hours, Metaxatos and Sriraj [1] and Khattak and Luo [8] found that the number of transgressions increase with an increasing platoon size.
On the other hand, small gain antennas will have lesser anomalies in the data but at the cost of lower overall sample size of pedestrian and cyclist's data.
Speck has found a strong correlation between street size and pedestrian activity.
As shown in figure 1, the size of pedestrian groups in population A follows a zero-truncated Poisson distribution (p = 0.06; on the basis of <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0010047.e001.PNG" class= inline-graphic"/> -test), in agreement with previous observations [15], [19].
The bicycle-transit catchment area is estimated as 1.7 and 2.3 times of the size of pedestrian-transit catchment area at home and activity ends respectively.
