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Published in:
2020 | OriginalPaper | Chapter
A Possibility of AI Application on Mode-choice Prediction of Transport Users in Hanoi
Authors : Truong Thi My Thanh, Hai-Bang Ly, Binh Thai Pham
Published in: CIGOS 2019, Innovation for Sustainable Infrastructure
Publisher: Springer Singapore
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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.