Abstract
This study investigated whether indices for socioeconomic, demographic and urban form characteristics can reflect the overall effect of each category in a demand forecasting model. Regression equations were developed for trip generation of the land use of long day care centres (LDCC) in the metropolitan region of Hobart, Australia, to estimate the morning peak hourly private car trip generation of the centres. The independent variables for the model were functions of socioeconomic, demographic and urban form related indices, while the dependent variable was private car trip generation per number of staff or children. Findings show that using indices for socioeconomic, demographic and urban form characteristics enhances overall model performance, while the models based on the commonly used method for estimating trip generation present acceptable results in just some specific sites. The use of socioeconomic, demographic and urban form indices can reflect differences in these characteristics across suburbs when estimating trip generation.
Highlights
Cities and countries have common types of land use
As Equation (2) shows, the effect of trip chaining has been considered by isolating the private car trip generation, for which the land use was the primary purpose of the trip, since only the non-chained trips constitute the additional traffic on the adjacent road
A comparison between the models created based on Equation (3) and the conventional method shows that the number of children as the long day care centres (LDCC)’s indicator performs better for estimating private car trip generation for both modelling methods
Summary
Cities and countries have common types of land use. For instance, residential land use is used for housing, and a childcare centre is a place which takes care of young children during working hours to allow parents to work. Developing a transport model that could describe the area-wide transport movements and travel behaviours require a large set of socioeconomic, demographic, and urban form data, which poses another significant and practical challenge [14] To deal with this issue, it would be useful to formulate socioeconomic, demographic and urban form characteristics into an index to reflect the overall effect of each category in a demand forecasting model. The study developed private car traffic generation models (considering the effect of trip chaining) for a selected land use by using socioeconomic, demographic and urban form indices as independent variables. Private car traffic generation with trip chaining effect was chosen for model development because traffic generation, mode choice and trip chaining are all traffic attributes that relate to land use type and change with changes to socioeconomic, demographic and urban form characteristics.
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