Abstract
Choices for various attributes of a trip are exercised by the trip maker in accordance with compatibility of his socio-economic level and the characteristics of the trip he is contemplating to undertake. Even though, discrete choice models developed based on the concept of utility maximisation are widely used in modelling the travel behaviour of individuals, the predictive ability of these models goes down drastically with the increase in the number of available alternatives. In this context, recent developments indicate that the Artificial Neural Network (ANN) is one emerging tool which can be very useful in modelling travel choice behaviour with large number of behavioural variables. This paper first explores the use of ANN for mode choice modelling through an analysis of choice of travel mode for access to mass transport (rail) in Mumbai. It also develops a comparison of ANN with the Multinomial Logit (MNL) model for identical data set. This comparison, in turn has been used as a means to provide further insight into the capability of ANN and showing its advantages in use for behavioural analysis.
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