Bicycle flow data is crucial for transportation agencies to evaluate and improve cycling infrastructure. Average annual daily bicyclists (AADB) is commonly used in research and practice as a metric for cycling studies such as ridership analysis, infrastructure planning, and injury risk. AADB is estimated by averaging the daily cyclist totals measured throughout the year using a long-term automated bicycle counter, or by using long-term bicycle counting data to extrapolate data from a short-term counting site. Extrapolation of a short-term bicycle counting site requires an accurate and complete set of daily factors from a group of references: long-term bicycle counters. In practice, validation of reference data is done manually, an exercise that is time-consuming but crucial as significant error can be introduced into AADB extrapolation if reference data are not validated. This paper proposes an automated method to validate long-term bicycle count data and interpolate anomalous portions of data. As part of this work, the methods are validated using a relatively large dataset of automated bicycle counts. For validation of our approach, data anomalies are created artificially in a way that removes data (first trial), or reduces counts to 25% or 40% of the measured bicycle counts (second and third trials), for 6 hours, 12 hours, and full days. Of the more than 100 generated anomalies, the validation process flagged approximately 90% in the first and second trials and 80% in the third trial. The average absolute relative error of the interpolated daily values was approximately 10% for all three trials.


    Access

    Download

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Automated Validation and Interpolation of Long-Duration Bicycle Counting Data


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2018-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Optimizing Short Duration Bicycle and Pedestrian Counting in Washington State

    K. Nordback / D. Johnstone / S. Kothuri | NTIS | 2017


    counting bicycle lock

    ROH SI JIN | European Patent Office | 2020

    Free access

    Performance Evaluation and Correction Functions for Automated Pedestrian and Bicycle Counting Technologies

    Proulx, Frank R. / Schneider, Robert J. / Miranda-Moreno, Luis F. | ASCE | 2016


    Performance Evaluation and Correction Functions for Automated Pedestrian and Bicycle Counting Technologies

    Proulx, Frank R. / Schneider, Robert J. / Miranda-Moreno, Luis F. | British Library Online Contents | 2016