Joint Modeling of Advanced Travel Information Service, Habit, and Learning Impacts on Route Choice by Laboratory Simulator Experiments

Abstract

A conceptual modeling framework is proposed, and mathematical submodels for route choice on motorways and urban networks are derived. The models convey the most relevant aspects that play a role in route choice, including learning, risk attitude under uncertainty, habit, and the impacts of advanced travel information service on route choice and learning. To gain insight into the relative importance of the different aspects and processes of route choice behavior, which support the proposed conceptual framework, the models were estimated with data from two experiments carried out with a so-called interactive travel simulator. The latter is a new research laboratory that combines the advantages of both stated preference and revealed preference research. Many relevant contributions on the aforementioned aspects that play a role in route choice can be found in the literature, but a simultaneous consideration of all is lacking. On the basis of these contributions from the literature, a conceptual framework that integrates these aspects was developed. The results from the laboratory experiments indicate that people perform best under the most elaborate information scenario and that habit and inertia together with en route information play a major role in route choice. Learning about route attributes is especially important during the first days but then plays a smaller role than the provided information and the developed habit. Finally, the way information is presented has a great impact on route choice.