An alternative approach to route choice simulation: the sequential models.

A path is, by definition, a sequence of links connecting an origin to a destination. As a consequence, two different approaches to the estimation of route choice probabilities can be considered in principle within the random utility theory which can be called "joint" and "sequential". The jointapproach assumes the user to choose a path among all those available for a given origin-destination pair, that is he/she jointly chooses all the links belonging to that path. The sequential approach assumes the user to reach his/her destination through a sequence of link choices at nodes; the choice probability of a path can be deduced by multiplying the choice probabilities of all the links belonging to that path. The main idea of this study is that, in route choice contexts, the simplification introduced by the user in his/her decisional process consists in adopting a sequential approach, i.e. "building" his/her route to reach the destination through successive link choices at nodes. During the learning process, the initial route is successively modified by substituting part of it with some others more efficient, i.e. by successively modifying one or more sequences of link choices. To simulate these link choices, taking into account the correlations mentioned above, different random utility model can be used and consistently different sequential route choice models are derived. In any case, this behavioural paradigm avoids the problem of identifying all available paths for any origin-destination pair. Moreover it generally leads to different link choice probabilities than those resulting from the joint approach - by definition they become independent from the trip origin - and consequently to different route choice probabilities. However, for two very well known route choice models - deterministic and Logit - the probabilities coincide in the two cases. In this study, different sequential route choice models are proposed and compared among each other and with the standard route choice models (Logit, C-Logit, Probit, etc.). Numerical results show the sequential models (above all the sequential Probit) perfectly ableto reproduce expected route choice probabilities in a number of test networks. Obviously from a computational point of view the performances of thesequential models are clearly much better. Dealing with new behavioural hypothesis, testing the models with experimental data is clearly particularly important. For the covering abstract see ITRD E135582.