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Recent mathematical models have been developed to explain and predict travel demand; they attempt to describe travel behavior via social science research techniques and theory. Two studies are reviewed which concern the analysis and use of attitudinal data to further enhance the understanding of urban travel. The first study's main objective is to develop a set of quantitative measures of comfort in order to describe that particular aspect of competing modes of intraurban travel. The second study analyzed a set of preference data collected as part of a feasibility study for innovative urban public transportation systems. Both studies employed multidimensional scaling techniques.
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