Abstract

The ability to forecast and to plan proactively for intercity travel patterns is a critical topic for many metropolitan areas. This paper sets forth, for use in travel demand modeling, a new typology of travelers on the basis of their annual intercity travel patterns. The typology was developed by using the 2013 Longitudinal Survey of Overnight Travel, which provided a year’s data and addressed the nonroutine nature of these long-distance trips. Annual summaries of intercity trips were compared, and travelers were categorized into six distinct segments by using the K-means cluster analysis. Each group clearly demonstrated a unique relationship with intercity travel and mode choices. A comparison of the typology with commonly used demographic variables highlighted the fact that such a characterization provided a deeper understanding of traveler preferences and biases than simply using demographics. The distribution of respondent demographics was relatively similar across each cluster and highlighted the need to consider factors beyond basic demographics when factors influencing long-distance travel decisions are being identified. This typology can significantly improve intercity demand models, either as an independent variable in disaggregate intercity travel demand models or as a region-level behavior-based characterization that provides meaningful contributions to the planning process. Specifically, the annual overnight intercity travel typology provides more information on travelers’ motivations and biases than other sociodemographic variables and thereby allows the model to be more responsive to policy and planning analyses and to provide more accurate forecasts.

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