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21.
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. 相似文献
22.
This paper introduces a vehicle transaction timing model which is conditional on household residential and job relocation
timings. Further, the household residential location and members’ job relocation timing decisions are jointly estimated. Some
researchers have modeled the household vehicle ownership decision jointly with other household decisions like vehicle type
choice or VMT; however, these models were basically static and changes in household taste over time has been ignored in nearly
all of these models. The proposed model is a dynamic joint model in which the effects of land-use, economy and disaggregate
travel activity attributes on the major household decisions; residential location and members’ job relocation timing decisions
for wife and husband of the household, are estimated. Each of these models is estimated using both the Weibull and log-logistic
baseline hazard functions to assess the usefulness of a non-monotonic rather than monotonic baseline hazard function. The
last three waves of the Puget Sound Panel Survey data and land-use, transportation, and built environment variables from the
Seattle Metropolitan Area are used in this study as these waves include useful explanatory variables like household tenure
that were not included in the previous waves. 相似文献