Qing-Yu Xiao

Publication Date


Document Type


First Advisor

Krmenec, Andrew J.

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Geography


Traffic flow--Illinois--Chicago Metropolitan Area


Recent literature reports that the increasing tripchaining behaviors (defined here as linking non-work trips to Journey-to-work trips) are most relevant to the rush-hour traffic of regular large-scale network congestion in metropolitan areas. In order to understand trip-chaining behavior in the three daily peak-hour periods, a conceptualized framework is established through the identification of six endogenous and exogenous determinant sets for trip-chaining propensity: three endogenous determinant sets (Trip Scheduling, Trip Frequency, Trip Mode Choice) and three exogenous determinant sets (Personal Characteristics, Household Structure, and Locational Factor). Based on the above established conceptual framework and the 1990 household travel survey data conducted by the Chicago Area Transportation Study (CATS), this thesis utilizes a Chi-square Test, an F-Test in discriminant analysis, and logistic regression to analyze and model the influence of the six determinant sets on the propensity for trip-chaining behavior during morning, noon and afternoon peak periods. The evidence from this study suggests that: First, trip-chaining propensity is associated with, or related to, three endogenous determinant sets. This indicates that chained work trips do trigger more traffic demand than unchained work trips; therefore, they will require more concern in the development of Travel Demand Management (TDM) policy. Second, trip-chaining propensity is associated with, or related to, three exogenous determinant sets. This indicates that chained work trips are more frequently made by those persons or households with particular personal attributes, household structure, and spatial commuting pattern. This finding may be used to improve the prediction of spatial pattern in peak-hour traffic demand. Third, the comparative analysis of trip-chaining propensity aunong three daily peak periods can bridge a gap in previous empirical studies, and thus provide a more systematic understanding of the determinants of tripchaining propensity.


Includes bibliographical references (pages [122]-124)


ix, 139 pages




Northern Illinois University

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