Path Choice Models in Stochastic Assignment: Implementation and Comparative Analysis - Di Gangi, Massimo; Polimeni, Antonio (Frontiers in Future Transportation, 2022)
In assignment models a key role is played by the path choice simulation that evaluates the path chosen by users in relation to the perceived paths and relative costs. This paper deals with the effects given by the implementation of some most adopted path choice models (Logit, Weibit, Probit and Gammit) within a Stochastic User Equilibrium assignment procedure. Some considerations on parameters needed to make results comparable one another and on the way to estimate them are also suggested; some extensions based on Weibit model are proposed. Results obtained both on a test network and on a real one are reported.