Metaanalysis of Travel Survey Methods

Abstract

Travel surveys often serve as the primary sources of information on travel demand characteristics. They provide critical data for transportation planning and decision making. In recent times, several factors motivate a comparative examination of travel survey methods. First, new travel demand modeling tools, such as those based on activity-based methods, are placing greater demands on travel behavior data gathered from household travel surveys. Second, response rates from household travel surveys have been showing a steady decline, possibly because of an increasingly survey-fatigued population. Third, declining resource availability at metropolitan planning agencies places emphasis on the need to maximize response rates to lower data collection costs per completed respondent. Ideally, a comparative examination of travel survey methods is best done through a carefully constructed experimental design that permits the isolation of the impact of various survey design parameters on response rates. However, the conduct of such a controlled experiment virtually is impractical. A metaanalysis of a sample of travel surveys conducted in the past 10 years is presented. A predictive model of response rates is developed by using linear regression techniques and the practical application of the model is demonstrated through several numerical examples.