Саяхат мінез-құлқы зерттеулері мен деректер жинау әдістері

Travel behavior is the study of what people do over geography, and how people use transport.

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. Such repeated surveys are useful because they yield different answers than surveys at a single point in time. 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. Today, the best source of information about travel behavior is a Household Travel Survey. In this type of data collection the sampling unit is the household and all its members because people interact the most with other people with whom they share a residence. Data on household characteristics, person characteristics, and a daily diary constitute the Household Travel Survey. The diary can be a trip diary (in which a person records every trip made in a day), or a place based diary (in which a person record every location visited, the trips made to reach these location and the activities completed), or a time use diary (in which a person everything he/she does in day). Examples include the National Household Travel Survey, the California Household Travel Survey, The Puget Sound Travel Survey. Data from these surveys can be found at https://www. nrel. gov/transportation/secure transportation data/.

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.