36: Simulating Household Travel Survey Data

Better (more comprehensive, higher quality, and more detailed) data on travel demand related to the sociodemographic and spatial characteristics of individuals and households are critical for modern transport planning and policy development. Provision of such data relies largely on household travel surveys (HTSs), in which a small sample of the population (usually about 2,000 to 5,000 households) records their travel patterns over some given time period. HTSs are notoriously expensive planning activities with current costs typically ranging from US$150 to US$200 per completed household, depending on the method used. Additionally, such surveys are plagued by non-participation and non- or misreporting from those who do participate – for instance, response rates of thirty to forty percent are considered about as good as can be achieved for other than face-to-face surveys (Greaves and Stopher, 2000). Given that most survey specialists maintain that any survey with less than a ninety percent response rate is potentially flawed, the implications for the quality and representativeness of the resulting data are startling.