[HTML][HTML] Machine learning approaches to bike-sharing systems: A systematic literature review

V Albuquerque, M Sales Dias, F Bacao - ISPRS International Journal of …, 2021 - mdpi.com
Cities are moving towards new mobility strategies to tackle smart cities' challenges such as
carbon emission reduction, urban transport multimodality and mitigation of pandemic …

A model framework for discovering the spatio-temporal usage patterns of public free-floating bike-sharing system

Y Du, F Deng, F Liao - Transportation Research Part C: Emerging …, 2019 - Elsevier
Public bike-sharing has gained much attention with the tide of sharing economy.
Empowered by modern technologies (eg, GPS devices and smartphone-based APPs), a …

A comparative analysis of e-scooter and e-bike usage patterns: Findings from the City of Austin, TX

MH Almannaa, HI Ashqar, M Elhenawy… - International Journal …, 2021 - Taylor & Francis
E-scooter-sharing and e-bike-sharing systems are accommodating and easing the
increased traffic in dense cities and are expanding considerably. However, these new micro …

[HTML][HTML] Passively generated big data for micro-mobility: State-of-the-art and future research directions

HH Schumann, H Haitao, M Quddus - Transportation Research Part D …, 2023 - Elsevier
The sharp rise in popularity of micro-mobility poses significant challenges in terms of
ensuring its safety, addressing its social impacts, mitigating its environmental effects, and …

[HTML][HTML] Bike-sharing demand prediction at community level under COVID-19 using deep learning

A Mehdizadeh Dastjerdi, C Morency - Sensors, 2022 - mdpi.com
An important question in planning and designing bike-sharing services is to support the
user's travel demand by allocating bikes at the stations in an efficient and reliable manner …

Exploring spatio-temporal pattern heterogeneity of dockless bike-sharing system: Links with cycling environment

W Gao, X Hu, N Wang - Transportation research part D: transport and …, 2023 - Elsevier
The demand balance for dockless bike-sharing systems (DBS) has become an important
concern for governments and operators. Due to its lack of fixed sites, DBS is significant …

Modeling bike counts in a bike-sharing system considering the effect of weather conditions

HI Ashqar, M Elhenawy, HA Rakha - Case studies on transport policy, 2019 - Elsevier
The paper develops a method that quantifies the effect of weather conditions on the
prediction of bike station counts in the San Francisco Bay Area Bike Share System. The …

Relocating operational and damaged bikes in free-floating systems: A data-driven modeling framework for level of service enhancement

X Chang, J Wu, H Sun, GH de Almeida Correia… - … Research Part A: Policy …, 2021 - Elsevier
Free-floating bike sharing is an innovative and sustainable travel mode, where shared bikes
can be picked up and returned at any proper place on the streets and not just at docking …

[HTML][HTML] Bike sharing and cable car demand forecasting using machine learning and deep learning multivariate time series approaches

C Peláez-Rodríguez, J Pérez-Aracil, D Fister… - Expert Systems with …, 2024 - Elsevier
In this paper the performance of different Machine Learning and Deep Learning approaches
is evaluated in problems related to green mobility in big cities. Specifically, the forecasting of …

Mobility pattern recognition based prediction for the subway station related bike-sharing trips

Y Lv, D Zhi, H Sun, G Qi - Transportation research part C: emerging …, 2021 - Elsevier
The free-floating bike-sharing (BS) system plays an important role in connection with the
public transit system. However, few studies have addressed the impacts of the subway …