Mode choice modelling in transportation planning is carried out through either traditional statistical techniques or artificial intelligence approach. Mode choice modelling presents a different scenario for researchers when considering border transport due to the inclusion of economic and policy measures such as gross domestic product (GDP). More work has been done for border transport modelling among countries which are politically or geographically connected such as members of the European Union (EU) countries. In spite of the usefulness of artificial intelligence techniques, logit models are more dominantly used for border transport modelling. Use of artificial intelligence (AI) techniques for mode choice modelling has been growing, and this trend is expected to continue in the future for border transport as well. This paper discusses the trends in mode choice modelling for intra-region and border transport, highlights the reasons for adopting different techniques, and suggests the future direction of research in the area of mode choice modelling.
Keywords: artificial intelligence, artificial neural networks, border transport, mode choice modelling