Abstract
Abstract. Decision makers develop transportation plans and models for providing sustainable transport systems in urban areas. Mode Choice is one of the stages in transportation modelling. Data mining techniques can discover factors affecting the mode choice. These techniques can be applied with knowledge process approach. In this study a data mining process model is applied to determine the factors affecting the mode choice with decision trees techniques by considering individual trip behaviours from household survey data collected within Izmir Transportation Master Plan. From this perspective transport mode choice problem is solved on a case in district of Buca-Izmir, Turkey with CRISP-DM knowledge process model.
Highlights
Modern transport systems should provide sustainability for everincreasing urban population and should correspond to the people’s need to move
Splitting rules were created from household survey data of Buca as training set with decision tree
This study focuses on factors affecting the mode choice that is one of the steps of transportation modelling by the perspective of individual trip behaviours
Summary
Modern transport systems should provide sustainability for everincreasing urban population and should correspond to the people’s need to move. Planners take into account transportation demand and habits of people living in cities for effective investments in transportation. For these reasons decision makers develop transportation plans and models. Transportation modelling provides local transportation solutions for urban planning. Stages in transportation modelling are listed as trip generation, trip distribution, mode choice, and assignments. Transportation modes could be revealed in urban areas. Cities should develop their own mode choice models based on local data. Transportation modelling has four stages, trip generation, trip distribution, mode choice, and assignment (Ortuzar & Williumsen, 2006). Mode choice as third stage includes decision of which modes (cars, bus, train etc.) must be used in transportation planning. As stated in Tye et al (1982) there are common orders of these factors by significance level
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