Individual Behavioural Models for Personal Transit Pre-trip Planners

Abstract

This paper presents the results of an in-progress research project aiming to define an advanced trip planner for transit networks. Starting from the description of user needs and logical architecture of the trip planner, the paper describes the module to support the user with pre-trip information based on his/her personal preferences. In particular the theoretical aspects of the individual, instead of user group (aggregate), path choice modelling used to support path choice set individuation, path utility calculation and user preference learning process are defined. The theoretical framework has been applied and tested through some experiments carried out on the public transport network of the metropolitan area of Rome.