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 …
Towards mobility data science (vision paper)
Mobility data captures the locations of moving objects such as humans, animals, and cars.
With the availability of GPS-equipped mobile devices and other inexpensive location …
With the availability of GPS-equipped mobile devices and other inexpensive location …
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 …
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 …
A data-driven approach for optimizing early-stage electric vehicle charging station placement
This paper presents a novel and practical data-driven approach to sub-optimally 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 …
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 …
Joint charging and relocation recommendation for e-taxi drivers via multi-agent mean field hierarchical reinforcement learning
Nowadays, most of the taxi drivers have become users of the relocation recommendation
service offered by online ride-hailing platforms (eg, Uber and Didi Chuxing), which could …
service offered by online ride-hailing platforms (eg, Uber and Didi Chuxing), which could …
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 …
Robust electric vehicle balancing of autonomous mobility-on-demand system: A multi-agent reinforcement learning approach
Electric autonomous vehicles (EAVs) are getting attention in future autonomous mobility-on-
demand (AMoD) systems due to their economic and societal benefits. However, EAVs' …
demand (AMoD) systems due to their economic and societal benefits. However, EAVs' …