3 citations · 4 across the 5 of their papers we have counts for
6 papers
Learning to Transfer Across Modes: Towards Unified Urban Mobility Forecasting
Yixuan Zhao, Man Luo
Urban transportation systems consist of multiple mobility modes that coexist within the same city and exhibit complex interdependencies, leading to correlated demand dynamics acros…
Toward Equitable Low-Carbon Mobility: Fairness-Aware Demand Prediction for Expanding Bike-Sharing Systems
Man Luo, Yixuan Zhao
Bike-sharing systems are an important component of low-carbon urban mobility, but continued expansion creates challenges in both cold-start prediction and equitable resource alloca…
Partially Observable Learning for Multi-Platform Dispatch Optimization
Fengming Yao, Man Luo
Instant delivery platforms have become a critical component of urban logistics, increasingly relying on crowdsourced couriers to fulfill highly dynamic orders. In real-world system…
Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning Approach
Man Luo, Bowen Du, Wenzhe Zhang +5
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…
Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search
Man Luo, Bowen Du, Konstantin Klemmer +2
Shared e-mobility services have been widely tested and piloted in cities across the globe, and already woven into the fabric of modern urban planning. This paper studies a practica…
Demand Prediction for Electric Vehicle Sharing
Man Luo, Hongkai Wen, Yi Luo +3
Electric Vehicle (EV) sharing systems have recently experienced unprecedented growth across the globe. Many car sharing service providers as well as automobile manufacturers are en…