When is big data big enough? Implications of using GPS-based surveys for travel demand analysis. (July 2015)

• Record Type: Journal Article
• Authors: Vij, Akshay; Shankari, K.
• Is Part Of: Transportation research. Volume 56(2015)
• Page Start: 446
• Page End: 462
• Publication Date: 2015-07
• Subjects: GPS-based surveys -- Travel diary surveys -- Travel demand models -- Inference error; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2015.04.025
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: We assess the implications of using GPS-based surveys for travel demand analysis. Multiple simulated datasets and real data are used. Errors in inference may offset gains in the volume of data. Benefits will vary with sample size, inference accuracy and model complexity. Abstract: A number of studies in the last decade have argued that Global Positioning Systems (GPS) based survey offer the potential to replace traditional travel diary surveys. GPS-based surveys impose lower respondent burden, offer greater spatiotemporal precision and incur fewer monetary costs. However, GPS-based surveys do not collect certain key inputs required for the estimation of travel demand models, such as the travel mode(s) taken or the trip purpose, relying instead on data-processing procedures to infer this information. This study assesses the impact that errors in inference can have on travel demand models estimated using data from GPS-based surveys and proposes ways in which these errors can be controlled for during both data collection and model estimation. We use simulated datasets to compare performance across different sample sizes, inference accuracies, model complexities and estimation methods. Findings from the simulated datasets are corroborated with real data collected from individuals living in the San Francisco Bay Area, United States. Results indicate that the benefits of using GPS-based surveys will vary significantly, depending upon the sample size of the data, the accuracy of the inference algorithm and the desired complexity of the travel demand model specification. In many cases, gains in the volume of data that can potentially be retrieved using GPS devices are found to be offset by the loss in quality caused by inaccuracies in inference. This study makes the argument that passively collected GPS-based surveys may never entirely replace surveys that require active interaction with study participants.