Mobility data science: Perspectives and challenges

M Mokbel, M Sakr, L **ong, A Züfle, J Almeida… - ACM Transactions on …, 2024 - dl.acm.org
Mobility data captures the locations of moving objects such as humans, animals, and cars.
With the availability of Global Positioning System (GPS)–equipped mobile devices and other …

Generative AI-empowered simulation for autonomous driving in vehicular mixed reality metaverses

M Xu, D Niyato, J Chen, H Zhang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
In the vehicular mixed reality (MR) Metaverse, the discrepancy between physical and virtual
entities can be overcome by fusing the physical and virtual environments with multi …

Deep learning for intelligent traffic sensing and prediction: recent advances and future challenges

X Fan, C **ang, L Gong, X He, Y Qu… - CCF Transactions on …, 2020 - Springer
With the emerging concepts of smart cities and intelligent transportation systems, accurate
traffic sensing and prediction have become critically important to support urban …

Characterizing internet card user portraits for efficient churn prediction model design

F Wu, F Lyu, J Ren, P Yang, K Qian… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Cellular Internet card (IC) as a new business model emerges, which penetrates rapidly and
holds the potential to foster a great business market. However, with the explosive growth of …

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 …

A data-driven approach for optimizing early-stage electric vehicle charging station placement

C Sun, T Li, X Tang - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
This article presents a novel and practical data-driven approach to suboptimally allocate
charging stations for electric vehicles (EVs) in an early-stage setting. Specifically, we …

An empirical analysis of electric vehicles' charging patterns

Z Li, Z Xu, Z Chen, C **e, G Chen, M Zhong - Transportation Research Part …, 2023 - Elsevier
Automotive electrification is a vital component of the carbon-neutrality agenda. To counter
the influence of shrinking public incentives for purchasing electric vehicles (EVs), it is crucial …

Data-driven distributionally robust electric vehicle balancing for autonomous mobility-on-demand systems under demand and supply uncertainties

S He, Z Zhang, S Han, L Pepin, G Wang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Electric vehicles (EVs) are being rapidly adopted due to their economic and societal
benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend …

FairCharge: A data-driven fairness-aware charging recommendation system for large-scale electric taxi fleets

G Wang, Y Zhang, Z Fang, S Wang, F Zhang… - Proceedings of the …, 2020 - dl.acm.org
Our society is witnessing a rapid taxi electrification process. Compared to conventional gas
taxis, a key drawback of electric taxis is their prolonged charging time, which potentially …

Large-scale vehicle trajectory reconstruction with camera sensing network

P Tong, M Li, M Li, J Huang, X Hua - Proceedings of the 27th Annual …, 2021 - dl.acm.org
Vehicle trajectories provide essential information to understand the urban mobility and
benefit a wide range of urban applications. State-of-the-art solutions for vehicle sensing may …