Capacity estimation of midblock bike lanes with mixed two-wheeled traffic

Lu Bai, Pan Liu, N. N. Sze, Amy Guo Haggart, Ching Yao Chan, Huaguo Zhou

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

The primary objectives of this study were to propose and validate a procedure for estimating the capacity of midblock bike lanes by taking into account the characteristics of three types of two-wheeled vehicle. The focus was on uninterrupted-flow midblock bike lanes on urban streets.We developed composite headway distribution models to identify the individual headway distributions of different types of two-wheeled vehicles, which were then aggregated to estimate the overall headway distribution based on their proportions in one lane. A distribution-free estimation approach was used to determine the key parameters of the composite headway distribution models. The proposed capacity estimation method was validated against field data which were collected at seven midblock bike lanes in Nanjing, China. Results suggest that the proposed procedure provides reasonable outcomes and can be used to estimate the capacities of midblock bike lanes with varying geometric design characteristics and traffic compositions.

Original languageEnglish
JournalTransportmetrica A: Transport Science
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Bike
  • bike lane
  • capacity
  • composite headway distribution
  • electric bike

ASJC Scopus subject areas

  • Transportation
  • Engineering(all)

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