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More than ever before, public transit must compete in the transport market. This competition is, on the one hand, against steadily increasing car traffic; and on the other hand, between public transit operators. This, in turn, leads to new demands regarding the type, content and quality of data needed for planning and management. Frequently, traditional travel behaviour surveys do not provide sufficiently accurate and detailed information about public transit demand. To plan public transit, frequently a precise description of all trip stages, including the first and the last mile, is necessary. To achieve this, an adaptation of the traditional survey methods is necessary. In many countries, public transit associations have been established to integrate services offered by individual public transit operators with the help of through-ticketing and a coordination of lines and timetables into what looks, to the user, like a single system. To distribute revenue among the operators involved, detailed surveys of passengers are needed. Measuring the quality of public transit service and surveying customer satisfaction are new tasks. Such data are the basis for quality assurance and are essential for gaining and keeping customers of the public transit system. New technologies such as the Global Positioning System, automated passenger counts and Smart Card Payment Systems offer new possibilities to collect data more efficiently and cost-effectively. This article covers essential aspects of surveys and the collection of data that are crucial for the planning and management of public transit; it points to state-of-the-art methods and offers potential solutions.

Purpose — In order to analyse applicability, comparability and limitations of GPS technology in travel surveys, different mobility survey techniques were tested in an Austrian pilot study.

Methodology/approach — Four groups of voluntary respondents recorded their travel behaviour over a time period of three consecutive days. The groups were assigned to three different and combined methods of data collection: Paper–pencil trip diaries, passive GPS tracking, active GPS tracking and prompted recall interviews.

Findings — The resulting mobility parameters show that self-reported paper– pencil surveys yield accurate sociodemographic information on the respondents as well as trip purposes and modes of transportation, although too few trips are reported. Passive GPS-based methods minimize the strain for respondents. Methods that combine GPS-based data collection and questionnaire provide the most reliable mobility data at the moment.

Research limitations/implications — Due to funding restrictions the sample sizes had to be relatively small (235 participants). Further development in research methodology will increase the effectiveness of automated data analysis, for example more accurate detection of activities and transport modes. The usefulness of GPS-based data collection in a large-scale surveys is planned to be tested in the next Austrian national travel survey.

Originality/value of paper — The pilot study allows a detailed comparison of traditional and GPS-based travel survey methods for the first time, due to data collection combined with prompted recalls.