Article ID: | iaor20116968 |
Volume: | 38 |
Issue: | 4 |
Start Page Number: | 697 |
End Page Number: | 714 |
Publication Date: | Jul 2011 |
Journal: | Transportation |
Authors: | Mohammadian Abolfazl, Rashidi Hossein |
Keywords: | demand, artificial intelligence: expert systems |
This paper presents a system of hierarchical rule‐based models of trip generation and modal split. Travel attributes, like trip counts for different transportation modes and commute distance, are among the modeled variables. The proposed framework could be considered as an alternative for several modules of the traditional travel demand modeling approach, while providing travel attributes at the highly disaggregate level that can be also used in activity‐based micro‐simulation modeling systems. Nonetheless, the modeling framework of this study is not considered as a substitute for activity‐based models. The explanatory variables set ranges from socio‐economic and demographic attributes of the household to the built environment characteristics of the household residential location. Another important contribution of the study is a framework in which travel attributes are modeled in conjunction with each other and the interdependencies among them are postulated through a hierarchical system of models. All the models are developed using rule‐based decision tree method. Moreover, the models developed in this study present a useful improvement in increasing the practicality and accuracy of the rule‐based travel data simulation models.