Recalibrating Adelaide’s strategic transport model
This study will develop a robust, efficient and cost-effective methodology for the recalibration of the South Australian strategic transport demand model (MASTEM) that does not rely on primary data collection methods.
In particular it will use household travel diary datasets collected in other jurisdictions within Australia to update MASTEM’s model parameters. Wherever possible, these datasets will be augmented with additional information available through the Census and other datasets regularly collected by the Australian Bureau of Statistics (ABS).
In some cases, model parameters will be updated based on established values reported in the literature. At its conclusion, the project will offer an updated set of parameter values for MASTEM, and a general methodology that can be used to continually update model parameters in the future.
Travel demand models (TDM) are quantitative tools that are used by local, regional and national planning organisations for the development of evidence-based transport policy. TDMs can offer insights on current patterns of travel behaviour and provide a framework for predicting changes in behaviour in response to changes in the transport system. Forecasts from TDMs are used to determine the capacity that new infrastructure must provide, and to facilitate the economic, environmental and social impact assessments of competing initiatives.
The Department of Infrastructure and Transport South Australia (DIT) is responsible for the delivery of effective planning policy, efficient transport systems, and valuable social and economic infrastructure in South Australia. DIT’s strategic TDM for the Greater Adelaide metropolitan area relies heavily on data from the 1999 Metropolitan Adelaide Household Travel Survey (MAHTS), which is now over 20 years old and as such not necessarily reflective of current or future travel patterns within the region. Hence, there is an urgent need to recalibrate and validate the existing model using more current data.
Traditionally, TDMs have been calibrated and validated using data collected through surveys that ask participating individuals about their travel patterns over a 1 or 2-day observation period. These data collection methods are expensive and inefficient. Hartgen and San Jose (2009) report1 average costs of $487,000 per survey, and roughly $150 per response, though they note that ”many surveys cost considerably more than the average, and the spread of the data is substantial”. For example, the ongoing Perth Area Travel Household Survey (PATHS) is expected to cost somewhere in the order of several millions of dollars upon completion.
As an alternative, transport planners in smaller urban areas that do not have the resources to invest in their own data collection exercises frequently use datasets from other comparable jurisdictions to calibrate their TDMs. In many cases, the parameters of the TDM may be borrowed directly from established values reported in the literature. For example, the US National Cooperative Highway Research Program (NCHRP)2 has drafted a best practices report on the calibration and validation of TDMs that includes procedures for transferring datasets across jurisdictions, and recommended values for a subset of standard model parameters (see Cambridge Systematics et al., 20123).
This study will apply this methodology to recalibrate MASTEM. In particular, we will use household travel diary datasets collected in other jurisdictions within Australia to update model parameters. Wherever possible, we will augment these datasets with additional information available through the Census and other datasets regularly collected by the Australian Bureau of Statistics (ABS). In some cases, we will update model parameters based on established values reported in the literature.
In summary, we will develop a robust, efficient and cost-effective methodology for the calibration of strategic transport demand models that does not rely on primary data collection methods.
The objective of this project is to develop and apply a methodology for recalibrating MASTEM model parameters that does not require primary data collection. In particular, this project will use a combination of the following existing sources of information to update MASTEM model parameters:
- Transport datasets from other jurisdictions within Australia, such as household travel diaries, freight movements and transport cost skims
- Demographic and transport datasets collected by the ABS within South Australia, such as the Australian Census, the Motor Vehicle Census, and the Road Freight Movements Survey
- Established model parameter values reported in the literature
Please note …
Ongoing, this page will be a living record of this project. As it continues, matures, hits milestones, etc., we’ll add information, links, images, interviews and more. Watch this space!
- Hartgen, D. T., & San Jose, E. (2009). Costs and trip rates of recent household travel surveys. Hartgen Group, Charlotte, NC, USA.
- Cambridge Systematics. (2012). Travel demand forecasting: Parameters and techniques(Vol. 716). National Cooperative Highway Research Program, Transportation Research Board.