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Mobility data science: Perspectives and challenges
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 …
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
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 …
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
With the emerging concepts of smart cities and intelligent transportation systems, accurate
traffic sensing and prediction have become critically important to support urban …
traffic sensing and prediction have become critically important to support urban …
Characterizing internet card user portraits for efficient churn prediction model design
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 …
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
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 …
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
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 …
charging stations for electric vehicles (EVs) in an early-stage setting. Specifically, we …
An empirical analysis of electric vehicles' charging patterns
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 …
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
Electric vehicles (EVs) are being rapidly adopted due to their economic and societal
benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend …
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
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 …
taxis, a key drawback of electric taxis is their prolonged charging time, which potentially …
Large-scale vehicle trajectory reconstruction with camera sensing network
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 …
benefit a wide range of urban applications. State-of-the-art solutions for vehicle sensing may …