Prompted recall travel surveying with gps

Using GPS technology in the collection of household travel data has been gaining importance as the technology matures. This paper documents recent developments in the field of GPS travel surveying and ways in which GPS has been incorporated into or even replaced traditional household travel survey methods. A new household activity survey is presented which uses automated data reduction methods to determine activity and travel locations based on a series of heuristics developed from land-use data and travel characteristics. The algorithms are used in an internet-based prompted recall survey which utilizes advanced learning algorithms to reduce the burden placed on survey respondents. Initial results of a small pilot study are discussed and potential areas of future work are presented.

Low data quality and heavy survey burden are standing issues in questionnaire-based household travel surveys (HTS). The proliferation of GPS and Internet-based geospatial technology provides great potential for innovation. This paper presents a web-based, geospatially prompted recall interview platform for GPS-based household travel survey. It made use of geospatial orientation and objects from Google Map as visual and semantic cues to prompt respondents’ recall of travel experiences. The realized system functionality includes end-user self-administrated passive GPS survey data uploading, web server database management for GPS and trip data, automated GPS data noise removal, trip/stop candidate extraction, and GPS trajectory simplification, as well as annotated trip visualization and playback animation. Several essential tools for trip editing and attribute updates are provided in a logical and user-friendly manner. This approach was tested in Shanghai, a metropolitan setting of dense population, heavy inner-city traffic, and cement forests. The preliminary results indicated that the Internet map-based interface offered a great deal of heuristics to improve trip recall accuracy, while the backstage data mining algorithms was able to tolerate greater errors in trip recall and attribution from the user. The combined effects of rich geospatial and semantic hints, short system response time, and friendly user interface may help to significantly reduce the physiological and mental burdens on survey respondents, hence leading to a higher rate of participation.

2010

For the past decade, GPS devices have been used increasingly as a means to validate household travel surveys and more recently as a means to determine response to travel behaviour change policies. However, although several papers have put forward arguments that GPS is now ready to be used as a potential substitute for conventional travel surveys, there has been somewhat of a reluctance to proceed in this direction. This paper describes such an effort. In late 2008, a team of consultants was put under contract by the Ohio Department of Transportation to conduct a GPS survey of households in the Greater Cincinnati area of southwest Ohio, northwest Kentucky, and southeast Indiana. A pilot survey was conducted in March-April 2009, and this paper reports on the outcome of that pilot study. At the time of writing this paper, the main study is underway, with a goal of having at least 3,000 households use GPS devices for a three-day period within the 12 months from mid-August 2009 to mid-August 2010. In this paper, the procedures for recruitment of households, delivery and collection of GPS devices, and the rates of completion of the survey are described. A prompted recall survey, using a web-based survey is also described. The purpose of the web-based prompted recall survey is to collect sufficient data to allow improvement and addition to existing processing software, so that the GPS data will provide sufficient information to allow travel demand models to be estimated, as well as informing various policy issues. Preliminary results from the pilot survey indicate some issues with completion of the GPS task and also with the prompted recall survey. These issues have suggested the use of variable incentives in the main survey to improve overall response levels and significant changes to the prompted recall survey, which have been implemented. Statistics are also provided on some of the sociodemographic characteristics of the pilot sample, and this is compared to Census data for the Greater Cincinnati area. However, it was not expected or intended that the pilot sample would be a representative sample of the population. Preliminary analysis of the data collected by GPS indicates a substantially higher rate of trip-making than has been measured in the past, using conventional diary methods. While this latter result was expected, the magnitude of the increase is larger than expected.

Transportation Research Part C: Emerging Technologies, 2012

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional surveyreported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPSrecorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-hour period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.

2000

Generally travel behavior data are collected by self-reported questionnaire surveys. Problems with these methods include lack of reporting for short trips, poor data quality on travel start and end times, travel times, and destination locations. The burden on the respondent is also very large. The detailed and accurate travel data should be needed to evaluate the effects of TDM strategies and ITS technologies on travel behavior, but it would be difficult using traditional questionnaire surveys. This paper aims to develop travel behavior data collecting systems using global positioning system (GPS), personal handyphone system (PHS) and geographic information system (GIS), and to examine the effectiveness of the data collected by these systems and the applicability for travel behavior surveys. We conducted the surveys of collecting travel behavior data by GPS and PHS, with travel and activity diary over a week. We collected GPS data of vehicle trips in two local cities from 15 and 28 commuters respectively, and PHS data of person trips of 30 people in a local city. Examples of day-to-day variability analyses of travel distances, times, speeds and routes of trips, are shown using data collected by GPS. We examined the characteristics of PHS data and the differences of travel start and end times, comparing PHS data with diary data, for elderly and non-elderly people. Also comparison between datasets of the two age groups was done. Improvements of these new systems for practical use to travel surveys are summarized.

Procedia - Social and Behavioral Sciences, 2012

The acquisition of travel data is currently based on cost-and time-intensive questionnaires and yields mostly an incomplete picture due to limited coverage and inadequate updates. There is an urgent need for technologically supported data acquisition tools. This paper introduces a novel approach to developing a large-scale travel survey by intelligently employing data from smartphones. Based on signals of the embedded accelerometers and GPS reveivers, an ensemble of probabilistic classifiers is trained for automatically reconstructing the individual trips composing a tour, including the mode choice. In the region of Vienna, Austria, 266 hours of travel data were collected to train and evaluate the models. Using a set of 72 features, the best classification results are achieved for detecting walks (92%) and bike rides (98%). Railway modes were correctly identified in 80% of all cases, which is subject to further research. In case of GPS losses only accelerometer data are used, which still shows promising results. This allows the method to incorporate places where there is normally only a weak or no GPS signal. Future smartphone applications are intended to spread the tool among traffic users, while the effort for them should be kept to a minimum i.e. no manual entries or questionnaires are necessary. Due to the increasing popularity of smartphones, the tool has the potential to be used on a widespread basis.

Transportation Research Record: Journal of the Transportation Research Board, 2012

Methodologically, the NHTS has evolved over the past 40 years. A list-assisted random-digit dialing sampling and computer-assisted telephone interviewing (CATI) technology were used for the recent . However, because sampling and interviews are based on landline telephones, certain population groups including university students are not properly represented in the NHTS (4). This flaw is partly because only a relatively small percentage of university students live with their parents in conventional households. In addition, many college students use only a mobile phone, and their mobile phone numbers are often not associated with the geographic area of the students' residences. In this regard, large-scale travel surveys targeting university students-the University Student Travel Survey (USTS)-were conducted in 2009 and 2010 at Old Dominion University (ODU) (N = 708, N = 1,468) and Virginia Polytechnic Institute and State University (VT) (N = 643, N = 1,128) to reveal their travel behavior (4-7). The USTS instrument design was based on the NHTS and was customized to university students.

2017

This study investigates methods to improve survey data quality and reduce response burden by sharing lessons learned from developing a household web-based survey platform (STAISI), along with field tests using novel features built into the platform. The field tests experiment with voluntary self and proxy reporting methods using a custom-built feature in the platform. The paper also compares the performance of the announce-in-advance and prompted recall technique in a web-survey setting. Finally, the paper presents key features of the platform and user interface recommendations for designing surveys that collect detailed trip data.

were consistently asked about the origin and final destination of each journey and stops made on the way. The hierarchical sequence was followed in the activity diary and CATI retrieval. The final data preserved the information about trip linkages within journeys. Information about trip chaining obtainable from BATS 2000 was compared to data from BATS 1996, which did not follow this protocol. The comparison of the trip-chaining indicators from both survey data sets shows much more trip-chaining activity in the BATS 2000 data file, which is attributed to the data collection and coding protocol. While the number of trip segments per person was only slightly higher in BATS 2000, this measure was significantly higher for not-employed men and women and employed women, age 45-64, indicating that these groups are likely to underreport trips if asked about them conventionally. Overall, the methods used in BATS 2000 provided consistent and richer information on trip chaining behaviour of respondents. 2 Activity and time-based approaches to travel demand modelling have greatly improved the ability of transportation planners to consider effects of changing technology and social trends on travel demand, air quality, and energy use. or example, current advances in communications technology are changing how people go about their daily activities and travel. Modelling air quality and energy use depends on information about trip patterns of individuals, including the types of vehicles they drive and detailed information about the starts and stops of these vehicles. Knowing what activities people engage in, and how new communication technologies can change where and when these activities take place allows planners to incorporate these changes into the travel forecasting process. Furthermore, knowing the reasons for trips and stops allows planners to estimate energy use and air quality for various scenarios based on the changes in travel patterns.

Transportation Research Record, 2002

This paper describes the results of an application of Internet survey methods to a household travel diary project. The project included a full field application of an Internet-based household travel diary instrument in a split sample design with conventional telephone/mail administration. The effects of this type of administration on survey response and on survey data are described. The work described in this paper demonstrates how Internet-based travel diary instruments can be used to complement other more traditional survey approaches. The Internet household travel diary instrument that was used here includes a number of features that take advantage of the computational power provided by modern servers and the graphical user interface provided by web browsers. Among these, the most important are detailed internal consistency checks that test the continuity and completeness of the activity/trip logs and interactive geocoding of trip ends. The response rates in the split sample conducted for the Las Cruces application indicate that providing an Internet option had a small positive effect. However, there are more pronounced effects on reported tripmaking -more trips reported in the Internet instrument, and on item nonresponse -lower rates with the Internet instrument. Overall, respondents who used the Internet instrument found it easy to use and appreciated having the option to complete the questionnaire at their convenience. There are clearly areas for further research, but it is equally clear that Internet-based household diary surveys can provide an important, cost-effective complement to CATI/mail methods.