Commute Warrior: An Android Application to Collect Longitudinal Travel Survey Data
Alper Akanser, Georgia Institute of Technology, Alice Grossman, Georgia Institute of Technology, Randall Guensler, Georgia Institute of Technology
Innovation in traditional travel surveys can benefit from technologies like GPS and interactive screens. We present an application that utilizes these technologies to increase completion rates and limit missed trips while addressing privacy concerns.
Traditional methods of travel survey data collection using paper mail out travel diaries suffer from high monetary costs, user fatigue, and response biases associated with data collection. Cutting edge research in travel surveys can help combat these drawbacks with innovative survey instruments that utilize current technology and monitored behavior. Recent advances in smartphone technology and the widespread market penetration of smartphones make it a viable and efficient platform to implement travel surveys for monitoring large populations over extended periods. The new interactive smartphone platform can drive innovation in traditional travel surveys to provide for more complete data sets, less expensive data collection processes, and an improved user experience. Smartphones also provide the advantage that people already voluntarily carry them almost all the time.
Mobile phone travel surveys utilize the Global Positioning Systems (GPS) devices to significantly enhance spatial and temporal accuracy in the data. Survey completion rates can be increased and missed trips can be reduced by providing the respondent with automatically-collected past trip data. The respondent can benefit in trip recollection and invest the time savings into providing more detailed and accurate responses to the surveys.
Georgia Tech researchers developed Commute Warrior, an Android application that passively collects travel data for long periods of time while minimizing battery use and providing privacy options to users. The collected travel data is processed by sophisticated server-side scripts to automatically delineate individual trips after removing noisy data. Commute Warrior presents this clean trip data to the respondent along with built-in interactive survey functionality to collect attitudinal data that enhance analysts’ ability to process and interpret the passively collected data. In addition, the high accuracy of the trip data makes more detailed analysis that depends on second-by-second data possible.
However, travel data collection systems based on smartphones do face challenges, such as limited battery power availability, privacy concerns, and a need to minimize interaction with users to avoid survey fatigue. Commute Warrior presents a simple dashboard for the respondent to stop all data collection, and adjust battery and communication settings. The surveys can be taken using the interactive screens of a smartphone providing great flexibility. The surveys provide interactive options and helpful data visualizations.
The Commute Warrior travel data collection system provides a rich dataset that can be used for studying driver behavior, travel time variability, and fuel consumption and emissions among other things. This paper details the features of the application, gives an overview of the Commute Warrior data collection system and presents some interesting data collected from the beta testers over the last two years.
Association for European Transport