Mode choice is a significant analysis of travel demand modelling. The selection of transport mode highly depends on the travel behavior of transport users, for instance, travel distance, trip cost, trip purpose, household income and so on. This study aims at investigating the possibility of applying Artificial Intelligent (AI) method to predict the mode choice through travel behavior survey data with a focus on Hanoi city - Vietnam. Firstly, travel interview survey was conducted with the involvement of 311 transport users at different land-use types. The study secondly applies the Ensemble Decision Trees (EDT) method to predict the mode-choice of transport users. Finally, the recommendation for a possibility of AI application on travel mode-choice is also proposed. The results of this study might beneficial for transport planners and transport authorities. The application of AI on parking demand forecast also contributes for the big data application on transport demand modeling.
A Possibility of AI Application on Mode-choice Prediction of Transport Users in Hanoi
Lecture Notes in Civil Engineering
2019-10-11
6 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Travel Behavior , Mode Choice , Machine learning , Ensemble Decision Trees Engineering , Geoengineering, Foundations, Hydraulics , Sustainable Development , Landscape/Regional and Urban Planning , Structural Materials , Building Construction and Design , Transportation Technology and Traffic Engineering
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