Simulation of Users Decision in Transport Mode Choice Using Neuro-Fuzzy Approach

In this paper, soft computing and artificial intelligence techniques have been used to define a model for simulating users' decisional process in a transportation system. Through this framework, the variables involved are expressed by approximate or linguistic values, like in the humans' reasoning way, in order to forecast users' mode choice behavior. The model has been specified and calibrated using a set of real life data. Results appear good in comparison with those obtained by a classical random utility based model calibrated with the same data, and the methodology seems promising also in case of different applications in the field of choice behavior simulation.