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Pedestrian and Bicycle Volume Data Collection Using Drone Technology

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  • Dohyung Kim

Abstract

Pedestrian and bicycle volume data is one of the most fundamental types of data for active transportation planning. However, they are not yet well developed. This paper explores an innovative method that uses drone technology to collect pedestrian and bicycle volume data. It confirms the feasibility of the technology as an alternative method to collect complex movements of pedestrians and bicycles. Furthermore, this paper presents a method that converts the video footage to a spatiotemporal dataset. The dataset includes not only the pedestrian and bicycle count data, but also their behavior and characteristics. The spatiotemporal data can become a valuable resource for a variety of active transportation planning practices and research, including the collection of pedestrian and bicycle volume data in parks and recreational areas, the study of collisions between pedestrians and bicycles, and the analysis of the social path. Since it is possible to envision that the development of technologies can overcome current technical difficulties, such as battery lifespan, it is worth considering the application of drone technology to active transportation planning practice and research.

Suggested Citation

  • Dohyung Kim, 2020. "Pedestrian and Bicycle Volume Data Collection Using Drone Technology," Journal of Urban Technology, Taylor & Francis Journals, vol. 27(2), pages 45-60, April.
    • Handle: RePEc:taf:cjutxx:v:27:y:2020:i:2:p:45-60
    DOI: 10.1080/10630732.2020.1715158
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    Cited by:

    1. Vujičić, Miroslav D. & Kennell, James & Stankov, Uglješa & Gretzel, Ulrike & Vasiljević, Đorđije A. & Morrison, Alastair M., 2022. "Keeping up with the drones! Techno-social dimensions of tourist drone videography," Technology in Society, Elsevier, vol. 68(C).
    2. Mohammad Anwar Alattar & Caitlin Cottrill & Mark Beecroft, 2021. "Sources and Applications of Emerging Active Travel Data: A Review of the Literature," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    3. Shereen Wael & Abeer Elshater & Samy Afifi, 2022. "Mapping User Experiences around Transit Stops Using Computer Vision Technology: Action Priorities from Cairo," Sustainability, MDPI, vol. 14(17), pages 1-20, September.

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