15 citations · 21 across the 18 of their papers we have counts for
3 papers · 1 filter
T-STAR: A Context-Aware Transformer Framework for Short-Term Probabilistic Demand Forecasting in Dock-Based Shared Micro-Mobility
Jingyi Cheng, Gonçalo Homem de Almeida Correia, Oded Cats +1
Reliable short-term demand forecasting is essential for managing shared micro-mobility services and ensuring responsive, user-centered operations. This study introduces T-STAR (Two…
Learning Personalized Utility Functions for Drivers in Ride-hailing Systems Using Ensemble Hypernetworks
Weiming Mai, Jie Gao, Oded Cats
In ride-hailing systems, drivers decide whether to accept or reject ride requests based on factors such as order characteristics, traffic conditions, and personal preferences. Accu…
Timing the Match: A Deep Reinforcement Learning Approach for Ride-Hailing and Ride-Pooling Services
Yiman Bao, Jie Gao, Jinke He +2
Efficient timing in ride-matching is crucial for improving the performance of ride-hailing and ride-pooling services, as it determines the number of drivers and passengers consider…