Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98055
PIRA download icon_1.1View/Download Full Text
Title: Capacity estimation of midblock bike lanes with mixed two-wheeled traffic
Authors: Bai, L
Liu, P
Sze, NN 
Haggart, AG
Chan, CY
Zhou, H
Issue Date: 2021
Source: Transportmetrica. A, Transport science, 2021, v. 17, no. 4, p. 1318-1341
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.
Keywords: Bike
Bike lane
Capacity
Composite headway distribution
Electric bike
Publisher: Taylor & Francis
Journal: Transportmetrica. A, Transport science 
ISSN: 2324-9935
EISSN: 2324-9943
DOI: 10.1080/23249935.2020.1859640
Rights: © 2021 Hong Kong Society for Transportation Studies Limited
This is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica A: Transport Science on 28 Jan 2021 (Published online), available at: http://www.tandfonline.com/10.1080/23249935.2020.1859640.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Sze_Capacity_Estimation_Midblock.pdfPre-Published version367.81 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

94
Last Week
4
Last month
Citations as of Nov 9, 2025

Downloads

90
Citations as of Nov 9, 2025

SCOPUSTM   
Citations

1
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

1
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.