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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.

Purpose — Describe the system set-up and processing requirements for a long-duration longitudinal Global Positioning System (GPS)/prompted-recall (PR) survey conducted in Sydney, Australia and assess reaction and cognition of participants.

Design/methodology/approach — The survey uses data collected using an in-car GPS device within a PR interface accessed over the Internet by participants. Technical requirements, interface design and survey administration of the survey are discussed. This is followed by an assessment of participant burden and cognition by analysing user activity on the PR and comparing participant responses to information inferred from the GPS data.

Findings — New technologies have allowed for increasingly sophisticated data collection efforts but they require substantial resources to translate this into a usable form. This study shows these technologies can be used to conduct long-duration travel studies in a way that is appealing and engaging to participants. However, it was found that responses to the PR are sometimes inconsistent and caution should be drawn in taking PR responses as the ‘ground truth’.

Research limitations/implications — The relatively low participant burden of this study shows long-duration studies are feasible if care is taken to limit the work required by participants. The inconsistency of the responses to the PR suggest future surveys may need to employ mechanisms that are better able to aid participants in accurately completing the survey.

Originality/value — Details the requirements of running a long-duration GPS/PR survey and assesses participant burden and cognition of the survey which are often not reported.

Over the past decade, transportation researchers have leveraged global positioning system (GPS) technology to improve the accuracy and increase the depth of spatial and temporal details obtained through household travel surveys. While earlier studies used GPS as a supplement to traditional household travel survey methods, measuring the accuracy of trips reported (Wolf et al., 2006), studies are now underway to identify the methods and tools that will allow us to do away with paper diaries entirely and simply rely on GPS to obtain trip details. This paper finds that while GPS clearly helps to improve participation among some groups, it decreases participation among others. Thus, it should be considered a tool in the household travel survey toolbox and not “the” solution to non-response issues in household travel surveys.

In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

Health scientists and urban planners have long been interested in the influence that the built environment has on the physical activities in which we engage, the environmental hazards we face, the kinds of amenities we enjoy, and the resulting impacts on our health. However, it is widely recognized that the extent of this influence, and the specific cause-and-effect relationships that exist, are still relatively unclear. Recent reviews highlight the need for more individual-level data on daily activities (especially physical activity) over long periods of time linked spatially to real-world characteristics of the built environment in diverse settings, along with a wide range of personal mediating variables. While capturing objective data on the built environment has benefited from wide-scale availability of detailed land use and transport network databases, the same cannot be said of human activity. A more diverse history of data collection methods exists for such activity and continues to evolve owing to a variety of quickly emerging wearable sensor technologies. At present, no “gold standard” method has emerged for assessing physical activity type and intensity under the real-world conditions of the built environment; in fact, most methods have barely been tested outside of the laboratory, and those that have tend to experience significant drops in accuracy and reliability. This paper provides a review of these diverse methods and emerging technologies, including biochemical, self-report, direct observation, passive motion detection, and integrated approaches. Based on this review and current needs, an integrated three-tiered methodology is proposed, including: (1) passive location tracking (e.g., using global positioning systems); (2) passive motion/biometric tracking (e.g., using accelerometers); and (3) limited self-reporting (e.g., using prompted recall diaries). Key development issues are highlighted, including the need for proper validation and automated activity-detection algorithms. The paper ends with a look at some of the key lessons learned and new opportunities that have emerged at the crossroads of urban studies and health sciences.

We do have a vision for a world in which people can walk to shops, school, friends' homes, or transit stations; in which they can mingle with their neighbors and admire trees, plants, and waterways; in which the air and water are clean; and in which there are parks and play areas for children, gathering spots for teens and the elderly, and convenient work and recreation places for the rest of us. (Frumkin, Frank, & Jackson, 2004, p. xvii)

In this chapter, we address the question if and how modern technology can be used to design questionnaires, diaries, web sites, and experiments to improve the validity of reliability of active data collection instruments. In particular, it discusses the history of computer-assisted activity diary data, reenactment sessions, stated preference methods, and interactive computer experiments with a special focus on the design of these instruments in terms of respondent support and user interfaces. Empirical evidence and experience suggests that although fascinating instruments may increase respondent motivation and involvement and therefore improve the reliability of the measurements, there is also the danger that respondents' answers are influenced by features of the electronic instrument that are not essential, reducing validity and reliability.

Purpose — The Department for Transport's 2011 GPS National Travel Survey (NTS) pilot study investigated whether personal GPS devices and automated data processing could be used in place of the 7-day paper diary. Using GPS technology could reduce the relatively high burden that the diary places upon respondents, reduce costs and improve data quality.

Design/methodology/approach — Data was collected from c.900 respondents. Practical changes were made to the existing methodology where necessary, including the collection of information to support data processing. Processing was undertaken using the University of Eindhoven's Trace Annotator. Results from the GPS pilot were then compared to those from the main NTS diaries for the same period.

Findings — There were no insurmountable problems using GPS devices to collect data; however, the processed GPS data did not resemble the diary outputs, making GPS unsuitable for the NTS. The GPS data produced fewer and longer trips than the diary data. The purpose of a quarter of the GPS trips was unclear, and a disproportionate share started and ended at home.

Research limitations — Further work to manually inspect trips identified via validation as unfeasible and subsequently refine the processing algorithms would have been desirable had time permitted. GPS data processing may have been hindered by missing GPS data, particularly in the case of rail travel.

Originality/value — This research used an accelerometer-equipped GPS device to better predict the method of travel. It also combined addresses that respondents reported having visited during the travel week with GIS data to code the purpose of trips without using a post-processing prompted-recall survey.

This book provides an international perspective on improving information to support transportation decision making. It comprises a selection of papers plus workshop syntheses from the 9th International Conference on Transport Survey Methods in Chile in November 2011. The conference was organized into 14 workshops with both paper presentations and discussions in the workshops forming the majority of the conference activity. The papers reported primarily on research pertaining to continuous improvement in transport survey methods — the backbone of the transportation data pipeline in most countries. But some papers also addressed the new ways in which innovation — notably technological innovation — is being applied to the capture and analysis of data to produce necessary information faster, better, and less expensively. The conference program built on a rich legacy of intellectual pursuits spanning the past two decades, and it is anticipated that the conference will continue into the future. Thus, the contents of this book represent a 5–10 year view through a moving window on the international state of the practice and concerns in transport survey methods.