Household Travel Surveys with GPS

Abstract

This paper documents the results of a pilot test done for the Oregon Household Travel Survey. The pilot was designed to enable the Oregon Department of Transportation to determine the role of a Global Positioning System (GPS) in the upcoming survey effort. Specifically, a three-pronged approach was employed. Households were randomly selected for inclusion in the study and then assigned to one of three groups: ( a) the traditional survey approach, ( b) the traditional approach with GPS, and ( c) GPS only. A total of 299 households from the city of Portland, Oregon, were recruited into the pilot, with 235 completing all required activities. A comprehensive evaluation of the similarities and differences in results across the three groups showed differences in respondent burden, completeness of travel details obtained, and costs. Results from this experiment also showed differences in nonresponse bias. The traditional survey had an expected nonresponse for the large households, low-income households, and young adults. Minority participation was on par with census figures. The GPS groups showed higher participation rates for young adults and nonminorities. These data confirmed the general thought that GPS was an effective tool for mitigating nonresponse among young adults. However, the minority nonresponse bias increased significantly with technology, suggesting that other methods would be more appropriate. With regard to completeness of data, geocoding rates are higher for the GPS groups, and there are significant differences in trip departure times, which could affect peak hour and time-of-day modeling. As expected, the costs were higher for the GPS groups, but the expectation is that these costs will fall as processes are standardized across studies and new technologies are introduced.

Misrecognition in a Sustainability Capital: Race, Representation, and Transportation Survey Response Rates in the Portland Metropolitan Area

“…They also help us advance a novel geographic data science approach-informed by justice and racial theories-for analyzing non-coverage and non-response errors and their relationship with misrecognized POCs in household travel surveys and their segregated and marginalized neighborhoods. Previous research has compared the representativeness between transportation surveys using geographic information systems, but such analyses pay limited attention to questions of racial and spatial representativeness as we have done in this study [15,87]. Further, those interested in analyzing household transportation survey representativeness may have difficulty accessing multiple household travel survey data that likely already misrepresent racial minorities and other marginalized populations.…”

“…Recent research in Portland, Oregon indicates that GPS technology is seen as a viable way to increase household transportation survey response rates, particularly for young adults. However, "the minority [non-response] bias increased significantly with technology, suggesting that other methods would be more appropriate" [87] (p. 51). The findings from the present study and corresponding arguments made elsewhere [1,2,15,17,[34][35][36][37] suggest that any implementation of the tailored design in the context of household travel surveys within and beyond Portland must recognize and attend to the significance of racialized experiences and identities in shaping where, how, and why people live, work, play, pray, learn, travel, and communicate.…”

Where Does Bicycling for Health Happen? Analysing Volunteered Geographic Information Through Place and Plexus

“…GPS travel survey methods including crowdsourced data sources such as Strava are beginning to bolster this research gap, though much remains to be done. The granularity and scalability of newer, bigger data helps overcome many of the obstacles common to traditional travel surveys, including response rates, memory and biases (Bricka, Zmud, Wolf, & Freedman, 2009;Shen & Stopher, 2014).…”

Understanding Route Switch Behavior: An Analysis Using GPS Based Data

“…As user memory largely influences stated choice data, they are often inaccurate and unreliable (Murakami and Wagner, 1999;Barbeau, et al, 2009). Technological progress, combined with the rapid advances in GPS devices, has resulted in major benefits for data collection, which now can be recorded automatically, in electronic format and, more importantly, with greater accuracy than those collected by means of individual interviews (Murakami and Wagner, 1999;Nakazato, et al, 2006;Hato, et al, 2006;Bricka, et al, 2009;Barbeau, et al, 2009). GPS has also been used to improve the knowledge of the attributes governing route choice (Jan, et al, 2000;Li, et al, 2005;Parkany, et al, 2006;Papinski, et al, 2009;Zhu and Levinson, 2009;Papinski and Scott, 2010;Zhu and Levinson, 2010;Spissu, et al, 2011;Levinson and Zhu, 2013).…”