North Carolina Department of Transportation
Research & Innovation Summit – 2020

Investigating Cycling Behavior Considering Different Temporal Characteristics Using Crowdsourced Bicycle Data

Authors: Zijing Lin, and Wei (David) Fan
UNCC
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Introduction

  • Crowdsourcing:
    “Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call.” (Howe, 2006)
  • Previous Research:
    • Mapping bicycle ridership (Jestico et al., 2016)
    • Analyzing cycling activities (Salon, 2016)
    • Estimating bicycle volume (Griffin and Jiao, 2015)
    • Public bicycle usage (Griffin and Jiao, 2019)
    • Modelling cycling route choice (Hood et al., 2011)
  • Primary Methods:
    • Generalized linear regression models (Hochmair et al., 2019)
    • Ordinal logistic regression models (Moore, 2015)
  • Research Gaps:
    • Few studies analysed the cycling behaviour for different temporal characteristics
    • Previous developed models for relevant research areas cannot address the unobserved heterogeneity within the data
  • Objectives:
    • To develop advanced mixed logit (MXL) models
    • To analyse the impact factors on cycling behaviour
    • To compare the cycling behaviour for different time periods

 

For questions about this research, contact Zijing Lin at zlin4@uncc.edu.