Travel surveys have always been a problematic, high-cost activity for metropolitan planning organisations. A method has been developed in the United States to synthesise household travel survey data from a combination of census and national transport survey data sources. The procedure involves creating distributions of pertinent variables (e.g. numbers of trips by purpose, mode and time of day of travel) that can be used to estimate travel-demand models. A sample of local residents is then drawn from disaggregate census data, providing detailed information on the socioeconomic characteristics of the sample. By using these characteristics, travel data are simulated from the transport data distributions by Monte Carlo simulation. This paper describes the application of this procedure to Adelaide, South Australia, for which an actual household travel survey exists from 1999. Results are compared between the synthetic and real data sets to determine the closeness of the match. After using travel characteristics derived from US data, it is concluded that the procedure performs about as well as the process was shown to perform in previous simulations for Dallas, Salt Lake City and Baton Rouge. This process holds out considerable promise for replacing the collection of larger and more expensive samples of household travel data, particularly for small and medium-sized urban areas.
|Original language||English (US)|
|Number of pages||16|
|Journal||Road and Transport Research|
|State||Published - Sep 2003|
ASJC Scopus subject areas
- Civil and Structural Engineering
- Mechanical Engineering