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Electric bike navigation comfort in pedestrian crowds

Kazemzadeh, Khashayar LU and Bansal, Prateek (2021) In Sustainable Cities and Society 69.
Abstract
The emergence of electric bikes (e-bikes) has brought a paradigm shift in shared mobility with a promise to move towards the mission of sustainable cities. Whereas an in-depth understanding of e-bike riding characteristics is
crucial to effectively design the infrastructure for active mobility, it remains an open area of research. We take the first step towards modelling the e-bike navigation comfort in pedestrian crowds. Through a laboratory controlled
field experiment, we collect trajectories of e-bike riders under different pedestrian crowding levels
in both opposite- (meeting) and same-direction (passing) encounters. For each trajectory, we obtain e-bike speed,
e-bike lateral distance, and pedestrian crowding after... (More)
The emergence of electric bikes (e-bikes) has brought a paradigm shift in shared mobility with a promise to move towards the mission of sustainable cities. Whereas an in-depth understanding of e-bike riding characteristics is
crucial to effectively design the infrastructure for active mobility, it remains an open area of research. We take the first step towards modelling the e-bike navigation comfort in pedestrian crowds. Through a laboratory controlled
field experiment, we collect trajectories of e-bike riders under different pedestrian crowding levels
in both opposite- (meeting) and same-direction (passing) encounters. For each trajectory, we obtain e-bike speed,
e-bike lateral distance, and pedestrian crowding after processing the data obtained from four stationary cameras.
Considering the riding comfort as a latent variable, we adopt a Bayesian network to represent the relationship between observed and the latent variables. Subsequently, we use fundamental principles of conditional probability to identify the causal effect of pedestrian crowding on e-bike riding comfort. Controlling for the demographic
heterogeneity, we also estimate the relationship between the comfort of an e-bike rider, pedestrian crowding, and her riding characteristics (e.g., speed and lateral distance). The results of this study would guide policymakers in ex-ante evaluations of the infrastructure decisions for active mobility. (Less)
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author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Sustainable Cities and Society
volume
69
article number
102841
pages
11 pages
publisher
Elsevier
external identifiers
  • scopus:85102878445
ISSN
2210-6707
DOI
10.1016/j.scs.2021.102841
language
English
LU publication?
yes
id
86bb7730-e1cc-4a1f-b73f-17f26f819de9
date added to LUP
2021-03-21 20:58:37
date last changed
2022-04-27 00:53:54
@article{86bb7730-e1cc-4a1f-b73f-17f26f819de9,
  abstract     = {{The emergence of electric bikes (e-bikes) has brought a paradigm shift in shared mobility with a promise to move towards the mission of sustainable cities. Whereas an in-depth understanding of e-bike riding characteristics is<br/>crucial to effectively design the infrastructure for active mobility, it remains an open area of research. We take the first step towards modelling the e-bike navigation comfort in pedestrian crowds. Through a laboratory controlled<br/>field experiment, we collect trajectories of e-bike riders under different pedestrian crowding levels<br/>in both opposite- (meeting) and same-direction (passing) encounters. For each trajectory, we obtain e-bike speed,<br/>e-bike lateral distance, and pedestrian crowding after processing the data obtained from four stationary cameras.<br/>Considering the riding comfort as a latent variable, we adopt a Bayesian network to represent the relationship between observed and the latent variables. Subsequently, we use fundamental principles of conditional probability to identify the causal effect of pedestrian crowding on e-bike riding comfort. Controlling for the demographic<br/>heterogeneity, we also estimate the relationship between the comfort of an e-bike rider, pedestrian crowding, and her riding characteristics (e.g., speed and lateral distance). The results of this study would guide policymakers in ex-ante evaluations of the infrastructure decisions for active mobility.}},
  author       = {{Kazemzadeh, Khashayar and Bansal, Prateek}},
  issn         = {{2210-6707}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Sustainable Cities and Society}},
  title        = {{Electric bike navigation comfort in pedestrian crowds}},
  url          = {{http://dx.doi.org/10.1016/j.scs.2021.102841}},
  doi          = {{10.1016/j.scs.2021.102841}},
  volume       = {{69}},
  year         = {{2021}},
}