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A Flexible and Integrated Methodology for Analytical Classification of Daily Travel-Activity Behavior

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  • Eric I. Pas

    (Duke University, Durham, North Carolina)

Abstract

The importance of incorporating the derived demand nature of urban person movement and the interdependence of the elemental travel episodes (trips) in analyses of urban travel behavior is discussed. A flexible and integrated approach to the analysis of daily urban travel-activity behavior as a complex phenomenon is described. The methodology incorporates systematic identification of classes of similar daily travel-activity patterns and the evaluation and interpretation of these groups. The approach described here comprises three stages; namely, transformation, group formation, and cluster interpretation and evaluation. In the first stage, raw input data describing the daily travel-activity patterns of a sample of individuals is transformed into a set of points in a real Euclidean space, where each point represents a daily travel-activity pattern. In the second stage, a cluster analysis algorithm is employed to identify groups of similar daily travel-activity patterns. In the third stage, the identified groups are interpreted by defining representative patterns for each group. Classifications produced by the methodology can be used to analyze and model relationships between daily travel-activity behavior and potential explanatory variables.

Suggested Citation

  • Eric I. Pas, 1983. "A Flexible and Integrated Methodology for Analytical Classification of Daily Travel-Activity Behavior," Transportation Science, INFORMS, vol. 17(4), pages 405-429, November.
  • Handle: RePEc:inm:ortrsc:v:17:y:1983:i:4:p:405-429
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    File URL: http://dx.doi.org/10.1287/trsc.17.4.405
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    Cited by:

    1. Siyu Li & Der-Horng Lee, 2017. "Learning daily activity patterns with probabilistic grammars," Transportation, Springer, vol. 44(1), pages 49-68, January.

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