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The questions studied in travel behavior are broad, and are probed through activity and time-use research studies, and surveys of travelers designed to reveal attitudes, behaviors and the gaps between them in relation to the sociological and environmental impacts of travel.
These questions can be answered descriptively using a travel diary, often part of a travel survey or travel behavior inventory. Large metropolitan areas typically only do such surveys once every decade, though some cities are conducting panel surveys, which track the same people year after year.
That data is generally used to estimate transportation planning models, so that transport analysts can make predictions about people who haven't been surveyed. This is important in forecasting traffic, which depends on future changes to road networks, land use patterns, and policies.
Some years ago it was recognized that behavioral research was limited by data, and a special data set was developed to aid research: The Baltimore Disaggregate Data Set which is the result an in depth survey, ca. 1977. Its title indicates today’s emphasis on disaggregated rather than aggregated data. This particular data set is believed lost. A small program to preserve and make available on the web these travel behavior surveys, the Metropolitan Travel Survey Archive, is now under way at the University of Minnesota. There is also the National Personal Transportation Survey (later National Household Travel Survey), conducted every five years or so, but with much less spatial detail.
Analysis of travel behavior from the home can answer the question: How does the family participate in modern society. Consider two non-observable extremes. At one extreme we have the non-specialized household. It does everything for itself, and no travel is required. Ultimate specialization is the other extreme; travel is required for all things. Observed households are somewhere in between. The “in between” position of households might be thought of as the consequence of two matters.
Moore (1964) has observed that increasing specialization in all things is the chief feature of social change. Considering social changes, one might observe that 100 years ago things were less specialized compared to today. So we would expect lots of change in household travel over the time period. Data are not very good, but the travel time aspect of what’s available seems contrary to the expectation, travel hasn’t changed much. For instance, the time spent on the journey to work may have been stable for centuries (the travel budget hypothesis). Here are some travel time comparisons from John Robinson (1986).
Most travel behavior analysis concerns demand issues and do not touch very much on supply issues. Yet when we observe travel from a home, we are certainly observing some sort of market clearing process – demand and supply are matched.
Analytic work on travel behavior can be dated from Liepmann (1945). Liepmann obtained and analyzed 1930s data on worker travel in England. Many of the insights current today were found by Liepmann: time spent, ride sharing, etc. Most academics date modern work from advances in mode choice analysis made in the 1970s. This created much excitement, and after some years an International Association for Travel Behaviour Research emerged. There are about 150 members of the Association; it holds a conference every three years. The proceedings of those conferences yield a nice record of advances in the field. The proceedings also provide a record of topics of lasting interest and of changing priorities. Mode choice received priority early on, but in the main today’s work is not so much on theory as it is on practice. Hagerstrand (1970) developed a time and space path analysis, often called the time-space prism.
On November 18–20, 2004, Transportation Research Board (TRB) held its third conference in Chicago, Illinois, with an interest in advancing the understanding of women’s issues in transportation. One of the presented studies, conducted by Nobis et al., revealed that the gender difference in travel patterns is linked to employment status, household structure, child care, and maintenance tasks. They found that travel patterns of men and women are much similar when considering single families; the differences are greater once males and females are compared in multi-person households without children; and are the highest once they live in households with children. Over the past two decades numerous studies have been conducted on travel behavior showing gender as an influential factor in travel decision making.
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