National travel profiles part B: trips, trends and travel predictions
Andrea Milne, Stacy Rendall, S Abley
Abstract
Andrea Milne, Stacy Rendall, S Abley
Abstract
Using data held within the New Zealand Household Travel Survey (NZHTS), this research examined changes in travel behaviour between 2003 and 2010 and sought to determine whether travel behaviours such as journey times, mode choice, trip complexity and trip generation rates differed by area type and region. A key aim of the research was to unlock further value from the data for the benefit of transport planners and engineers. The research explored the extent to which NZHTS data could be used in a predictive context and examined a method to extract and arrange the NZHTS data into a form that would allow practitioners to quickly undertake a range of enquiries based on user-specified variables such as car ownership and household compositions to reveal area-specific travel behaviours. The research provided an additional reference source for policy makers by allowing them to view changes in travel behaviours over time that might be attributed, in part, to past and present transport policy. The research findings offer an addition to multi-modal trip generation resources for the benefit of traffic engineers and can also assist travel planning coordinators to achieve the most effective use of existing transport resources.
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Using data held within the New Zealand Household Travel Survey (NZHTS), this research examined changes in travel behaviour between 2003 and 2010 and sought to determine whether travel behaviours such as journey times, mode choice, trip complexity and trip generation rates differed by area type and region. A key aim of the research was to unlock further value from the data for the benefit of transport planners and engineers. The research explored the extent to which NZHTS data could be used in a predictive context and examined a method to extract and arrange the NZHTS data into a form that would allow practitioners to quickly undertake a range of enquiries based on user-specified variables such as car ownership and household compositions to reveal area-specific travel behaviours. The research provided an additional reference source for policy makers by allowing them to view changes in travel behaviours over time that might be attributed, in part, to past and present transport policy. The research findings offer an addition to multi-modal trip generation resources for the benefit of traffic engineers and can also assist travel planning coordinators to achieve the most effective use of existing transport resources.
Key concepts: TRIPS architecture, Travel survey, Travel behavior, Trip generation, Context (archaeology), Transport engineering, Mode choice, Modal