M.N. Postorino and M. Versaci
Mode choice, decision rules, fuzzy systems, neuro-fuzzy inferences
Increasing congestion on the main roads in urban areas pushes analysts to improve simulation of modal choice to obtain good estimation of the demand shares for different travel modes. In the literature, several kinds of behavioural models have been proposed in order both to evaluate the modal choice percentage in urban areas and to capture the travel behaviour by means of the estimation of some suitable parameters. However, behaviour is complex in itself and often standard models, even if sophisticated, cannot capture all the complex mechanisms underlying the user behaviour. In this paper, a neuro-fuzzy approach is proposed to extract the mode choice decision rules of travel users, by evaluating different sets of rules and different membership functions. Particularly, to determine which inputs are the most relevant in such decision process, fuzzy curves and surfaces have been taken into account. In this way, nonlinear effects can be considered.
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