Electric bike navigation comfort in pedestrian crowds
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/86bb7730-e1cc-4a1f-b73f-17f26f819de9
- author
- Kazemzadeh, Khashayar LU and Bansal, Prateek
- organization
- publishing date
- 2021
- 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}}, }