Household travel surveys (HTS) are traditionally conducted every decade or so, providing planning agencies with comprehensive data on travel patterns in a region. The infrequency coupled with the rigorous sampling design and large sample size of a HTS make the survey an attractive opportunity for agencies to also measure regional attitudes to contemporary or upcoming planning challenges, such as potential new transportation options. One efficient way to quantify preferences and attitudes is stated preference (SP) experiments, in which respondents choose between a set of travel modes and thereby reveal preferences between attributes of each option. Until recently, SP surveys have typically been administered separately from the HTS. As web-based survey instrument technologies continue to advance there is opportunity to present stated preference experiments in real-time based upon details of trips reported in the HTS diary, and thus offering agencies opportunities for cost savings and richer datasets.

As part of their first household travel survey in over 30 years, the Madison County Council of Governments, Indiana, deployed a web-based stated preference survey within their household travel survey to quantify interest in two hypothetical future transit modes - express bus and commuter rail - as alternatives to the approximately 40 mile drive to Indianapolis. The objective was to gather data from a cross section of the area’s population – both frequent and infrequent travelers to the state capital. The 1,340 qualifying respondents saw five stated preference experiments with varying levels of travel time, travel cost or transit fare, parking cost, and transit frequency.

This paper presents and evaluates the opportunities and complexities involved in designing and conducting a set of exploratory stated preference experiments based upon trips reported within a HTS, all while ultimately providing additional value to an agency. The paper addresses balancing between the broadly relevant and sufficiently specific; designing the behavioral and geographic screening criteria necessary for an adequate sample size and desirable range of travel behaviors, accommodating frequent and infrequent travelers alike, customizing the experiments including creating logic for trip selection hierarchy, and how best to limit respondent burden.