Graph neural network for traffic forecasting: A survey

W Jiang, J Luo - Expert systems with applications, 2022 - Elsevier
Traffic forecasting is important for the success of intelligent transportation systems. Deep
learning models, including convolution neural networks and recurrent neural networks, have …

A systematic literature review on machine learning in shared mobility

J Teusch, JN Gremmel, C Koetsier… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Shared mobility has emerged as a sustainable alternative to both private transportation and
traditional public transport, promising to reduce the number of private vehicles on roads …

[HTML][HTML] A data-driven framework for medium-term electric vehicle charging demand forecasting

A Orzechowski, L Lugosch, H Shu, R Yang, W Li… - Energy and AI, 2023 - Elsevier
The rapid phase-in of electric vehicles (EV) will cause unprecedented issues with managing
the supply of electricity and charging stations. It is in the interest of utility providers and …

The right tools for the job: The case for spatial science tool‐building

G Boeing - Transactions in GIS, 2020 - Wiley Online Library
This article was presented as the 8th annual Transactions in GIS plenary address at the
American Association of Geographers annual meeting in Washington, DC. The spatial …

Towards accessible shared autonomous electric mobility with dynamic deadlines

G Wang, Z Qin, S Wang, H Sun… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Shared autonomous electric mobility has attracted significant interest in recent years due to
its potential to save energy consumption, enhance mobility accessibility, reduce air pollution …

Sharing instant delivery UAVs for crowdsensing: A data-driven performance study

J Gao, Y Pan, X Zhang, Q Han, Y Hu - Computers & Industrial Engineering, 2024 - Elsevier
In recent years, there has been a significant increase in demand for instant deliveries, such
as rapid delivery of takeaway food and medicine. Many logistics companies are planning to …

A predictive vehicle ride sharing recommendation system for smart cities commuting

T Anagnostopoulos - Smart Cities, 2021 - mdpi.com
Smart Cities (or Cities 2.0) are an evolution in citizen habitation. In such cities, transport
commuting is changing rapidly with the proliferation of contemporary vehicular technology …

Fleet rebalancing for expanding shared e-Mobility systems: A multi-agent deep reinforcement learning approach

M Luo, B Du, W Zhang, T Song, K Li… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
The electrification of shared mobility has become popular across the globe. Many cities have
their new shared e-mobility systems deployed, with continuously expanding coverage from …

Socially-equitable interactive graph information fusion-based prediction for urban Dockless E-scooter sharing

S He, KG Shin - Proceedings of the ACM Web Conference 2022, 2022 - dl.acm.org
Urban dockless e-scooter sharing (DES) has become a popular Web-of-Things (WoT)
service and widely adopted globally. Despite its early commercial success, conventional …

Understanding user behavior in car sharing services through the lens of mobility: Mixing qualitative and quantitative studies

G Wang, HR Vaish, H Sun, J Wu, S Wang… - Proceedings of the ACM …, 2020 - dl.acm.org
Qualitative and quantitative user studies can reveal valuable insights into user behavior,
which in turn can assist system designers in providing better user experiences. Car sharing …