Quantifying the impact of COVID-19 on e-bike safety in China via multi-output and clustering-based regression models. [PDF]
PLoS ONE, 2021 The impacts of COVID-19 on travel demand, traffic congestion, and traffic safety are attracting heated attention. However, the influence of the pandemic on electric bike (e-bike) safety has not been investigated.
Xingpei Yan, Zheng Zhu
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Exploring built environment factors on e-bike travel behavior in urban China: A case study of Jinan [PDF]
Frontiers in Public Health, 2022 E-bike, characterized as a low-carbon and health-beneficial active travel mode, is gradually becoming popular in China. Although built environment factors are considered to be key parameters that can facilitate or hinder active transportation, such as ...
Yonghao Yu +5 more
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Public employees in South-Western Norway using an e-bike or a regular bike for commuting – A cross-sectional comparison on sociodemographic factors, commuting frequency and commuting distance [PDF]
Preventive Medicine Reports, 2019 Large-scale analyses on the travel behavior of e-bikes are scarce, and current knowledge regarding who the e-bike owners are is inconsistent. Also, commuters represent a relevant user group with an unexploited potential.
Anette B. Jahre +6 more
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Riding practices of e-bike riders after the implementation of electric bike management regulations: An observational study in Hangzhou, China [PDF]
HeliyonObjective: This study aimed to understand the riding behaviors of electric bike (e-bike) users in Hangzhou after the “Regulations of Zhejiang Province on the Administration of Electric Bicycles”.
Jue Xu +9 more
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Behavior change interventions to promote adoption of e-bike shared mobility in a rural area: evidence from a mixed-method field trial [PDF]
Frontiers in PsychologyEncouraging a shift to sustainable travel modes is essential for achieving net zero goals. This mixed-method study investigates the adoption of e-bike shared mobility in a rural context.
Mark Wilson +3 more
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Identify Risk Pattern of E-Bike Riders in China Based on Machine Learning Framework [PDF]
Entropy, 2019 In this paper, the risk pattern of e-bike riders in China was examined, based on tree-structured machine learning techniques. Three-year crash/violation data were acquired from the Kunshan traffic police department, China.
Chen Wang, Siyuan Kou, Yaochao Song
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HELMET (HEaLth iMpact of E-bikes and e-scooTers) study: Data collection methods and information gathered for the evaluation of the introduction of share-hire schemes [version 2; peer review: 2 approved, 1 approved with reservations] [PDF]
NIHR Open ResearchBackground This study aimed to collect and summarise information on e-bike and e-scooter use in areas with and without e-bike (EB) and e-bike plus e-scooter (EB+ES) combined share-hire schemes.
James Garbutt +10 more
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Improving E-Bike Safety on Urban Highways in China [PDF]
Discrete Dynamics in Nature and Society, 2015 This paper aims to examine characteristics of e-bike fatal crashes on urban highways in China. Crash data were retrieved from the three-year crash reports (2010–2012) of Taixing City.
Linjun Lu, Chen Wang, Tao Wang
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[E-scooter, e-bike and bicycle injuries in the same period-A prospective analysis of a level 1 trauma center]. [PDF]
Unfallchirurgie (Heidelb), 2023 Meyer HL +7 more
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Risk Factors for Road-Traffic Injuries Associated with E-Bike: Case-Control and Case-Crossover Study. [PDF]
Int J Environ Res Public Health, 2022 Zhong Z, Lin Z, Li L, Wang X.
europepmc +3 more sources