Modelling route choice decision making in Advanced Traveler information System (ATIS) contexts is still a crucial task. In particular, two main categories of variables can be identified in order to model travelers’ behaviors: the former may be defined as endogenous and are related to the experiment environment; the latter may be defined as exogenous (referring to the respondents involved in the experiment). This paper focuses on the analysis of exogenous variables. An experiment is carried out using a driving simulator, on a real route choice context (a sub-area of the urban network in the city of Naples, in the Campania Region) reproduced in a virtual reality. All data are analyzed by aggregate and statistical approaches to preliminarily investigate the correlations between some exogenous variables and the collected choices of drivers. Furthermore, collected observations have been modelled by applying the Structural Equation Model (SEM) approach to model the effect of information on switching behaviors.

Modelling Behavior in a Route Choice Driving Simulation Experiment in Presence of Information

Roberta Di Pace
;
Stefano de Luca;
2021-01-01

Abstract

Modelling route choice decision making in Advanced Traveler information System (ATIS) contexts is still a crucial task. In particular, two main categories of variables can be identified in order to model travelers’ behaviors: the former may be defined as endogenous and are related to the experiment environment; the latter may be defined as exogenous (referring to the respondents involved in the experiment). This paper focuses on the analysis of exogenous variables. An experiment is carried out using a driving simulator, on a real route choice context (a sub-area of the urban network in the city of Naples, in the Campania Region) reproduced in a virtual reality. All data are analyzed by aggregate and statistical approaches to preliminarily investigate the correlations between some exogenous variables and the collected choices of drivers. Furthermore, collected observations have been modelled by applying the Structural Equation Model (SEM) approach to model the effect of information on switching behaviors.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4765222
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