Challenges and Opportunities of Emerging Data Sources to Estimate Network-Wide Bike Counts
Emerging sources of mobile location data such as Strava and other phone-based apps may provide useful information for assessing bicycle activity on each link of a network. Despite their potential to complement traditional bike count programs, the representativeness and suitability of these emerging sources for producing bicycle volume estimates remain unclear. This study investigates the challenges and opportunities by fusing Strava data with short-term and permanent conventional count program data to produce bicycle volume estimations using clustering and nonparametric modeling. Analysis indicates that the concentration of permanent counters at high bicycle volume locations presents a significant challenge to produce network-wide daily volume estimations even though Strava data demonstrate potential in mitigating the estimation bias at lower-volume sites. Despite the contribution of Strava to develop reliable and spatially and temporally transferable bicycle volume estimations, significant challenges remain to rely on Strava counts alone to characterize network-level activities due to sampling bias and spatial representations. This study will help planners discern and assess the challenges and opportunities of using emerging data in bicycle planning.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/24732907
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Supplemental Notes:
- © 2021 American Society of Civil Engineers.
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Authors:
- Miah, Md Mintu
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0000-0001-6073-3896
- Hyun, Kate Kyung
- Mattingly, Stephen P
- Broach, Joseph
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0000-0001-7753-501X
- McNeil, Nathan
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0000-0002-0490-9794
- Kothuri, Sirisha
- Publication Date: 2022-3
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: 04021122
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Serial:
- Journal of Transportation Engineering, Part A: Systems
- Volume: 148
- Issue Number: 3
- Publisher: American Society of Civil Engineers
- ISSN: 2473-2907
- EISSN: 2473-2893
- Serial URL: http://ascelibrary.org/journal/jtepbs
Subject/Index Terms
- TRT Terms: Bicycle counts; Data fusion; Mobile applications; Networks; Traffic counting stations; Traffic data
- Identifier Terms: Strava (Computer software)
- Subject Areas: Data and Information Technology; Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting;
Filing Info
- Accession Number: 01837751
- Record Type: Publication
- Files: TRIS, ASCE
- Created Date: Feb 28 2022 9:42AM