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Are we there yet? Assessing smartphone apps as full-fledged tools for activity-travel surveys

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Abstract

Given the limitations of traditional methods of data collection and the increased use of smartphones, there is growing attention given to using smartphone apps for activity-travel surveys. Smartphones, through their location-logging capability, allow for the collection of high-quality data on the travel patterns of individuals over multiple days while minimizing the burden on those being monitored. This paper presents the results of an investigation into the potential and limitations of smartphone apps as passenger travel survey instruments. It evaluates the accuracy and performance of various smartphone apps using properly recorded ‘ground truth’ data. Through an open and global invitation to travel survey app and trace processing suite developers, a total of 17 apps were recruited for testing. A controlled experiment was devised, and the accuracy of the apps evaluated based on their ability to reproduce ground truth trip information. Further, the performance of the apps in terms of battery drain was also quantified and evaluated. Results indicate that while accuracy in terms of the trip ends/starts is reasonably high in most cases, mode inference accuracy varied significantly, with a maximum 65–75% accuracy achieved. As such, until significant improvements in mode inference algorithms arise, purely passive location-logging smartphone apps cannot serve as full-fledged automated travel survey instruments. While this may seem problematic, with minor input from respondents regarding regularly visited locations and modes used, as well as specific test case tuning and use of external data such as General Transit Feed Specification, there is an excellent potential to significantly reduce overall response burden and allow for high quality multi-day travel diary data to be collected. Implications of our findings for app design are discussed.

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Notes

  1. In this paper, trips refer to movements from an origin to a destination. If a trip includes more than one mode, legs are the individual mode segments of a trip that get from origin to mode change point, between mode change points if more than one mode is used, and between the final mode change point and the trip destination. Finally, links refer to the road network links traveled on during the course of a movement episode (this in contrast with a stationary episode). These are drawn as polylines between intersections.

  2. While the success of a travel diary data collection project depends just as much on recruitment and design of user interface as it does on the more technical accurate recording and processing of traces, the design aspect of the work would have meant an entirely different project being undertaken. For more information on more human elements of app design dealing with user experience design, the readers are referred to one of the appendices in Harding (2019).

  3. The cut-off values in this paper were decided upon after trial and error testing in a previous project by the same team, taking Toronto subway spacing, network attributes such as block size and minimum dwell times into consideration (Miller et al. 2016). The data collection protocol was compatible with the values previously determined using trial and error, namely staying in a given location for 3 min or more before beginning another travel episode.

  4. People ‘access’ modes higher up in the hierarchy using modes below. While there can be cases where a trip’s access mode might be longer than the ‘main’ mode assigned (ex: if a suburbanite drives 30 km to a subway station, parks there and then takes the subway into town the last few kilometers), in more cases we would be dealing with walk or bike access to transit, as well as drive access to commuter rail.

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Acknowledgements

This study was funded by the Transportation Information Steering Committee for the Greater Toronto-Hamilton Area. The authors are solely responsible for all comments and interpretations presented in the paper. An abridged version of the paper was presented at the 2020 Annual Transportation Research Board Conference.

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Authors and Affiliations

  1. Systems Analysis and Forecasting Office, Ontario Ministry of Transportation, Toronto, Canada

    Chris Harding

  2. Civil and Environmental Engineering, Imperial College London, London, UK

    Ahmadreza Faghih Imani

  3. RATIO.CITY, Toronto, Canada

    Siva Srikukenthiran

  4. Civil and Mineral Engineering, University of Toronto, Toronto, Canada

    Eric J. Miller & Khandker Nurul Habib

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  1. Chris Harding
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  2. Ahmadreza Faghih Imani
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  3. Siva Srikukenthiran
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  4. Eric J. Miller
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  5. Khandker Nurul Habib
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Contributions

The authors confirm contribution to the paper as follows: study conception and design: C. Harding, A. F. Imani, S. Srikukenthiran, K. M. N. Habib, E. J. Miller; data collection: C. Harding; analysis and interpretation of results: C. Harding, A. F. Imani; draft manuscript preparation: C. Harding, A. F. Imani; overall project supervision: K. M. N. Habib. All authors reviewed the results and approved the final version of the manuscript.

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Correspondence to Ahmadreza Faghih Imani or Khandker Nurul Habib.

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Harding, C., Faghih Imani, A., Srikukenthiran, S. et al. Are we there yet? Assessing smartphone apps as full-fledged tools for activity-travel surveys. Transportation 48, 2433–2460 (2021). https://doi.org/10.1007/s11116-020-10135-7

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