Hmdrl: Hierarchical mixed deep reinforcement learning to balance vehicle supply and demand

J Xi, F Zhu, P Ye, Y Lv, H Tang… - IEEE Transactions On …, 2022 - ieeexplore.ieee.org
The imbalance of vehicle supply and demand is a common phenomenon that influences the
efficiency of online ride-hailing systems greatly. To address this problem, a three-level …

ForETaxi: data-driven fleet-oriented charging resource allocation in large-scale electric taxi networks

G Wang, Y Chen, S Wang, F Zhang… - ACM Transactions on …, 2023 - dl.acm.org
Charging processes are the key to promoting electric taxis and improving their operational
efficiency due to frequent charging activities and long charging time. Nevertheless …

Joint order dispatch and charging for electric self-driving taxi systems

G Fan, H Jin, Y Zhao, Y Song, X Gan… - … -IEEE Conference on …, 2022 - ieeexplore.ieee.org
Nowadays, the rapid development of self-driving technology and its fusion with the current
vehicle electrification process has given rise to electric self-driving taxis (es-taxis) …

Optimizing Profitability of E-Scooter Sharing System via Battery-aware Recommendation

J Kim, T Jung, Y Choi, D Kim, H Cha - Proceedings of the 22nd Annual …, 2024 - dl.acm.org
In e-scooter sharing systems, users randomly select and use e-scooters based on
inaccurate battery information. This simple rental policy leads to low profitability on two …

Data-Driven Optimization Models for Shared Mobility-on-Demand Systems

X Li - 2022 - spectrum.library.concordia.ca
Shared Mobility-on-Demand (MoD) has tremendously reshaped the transportation patterns
in urban areas. The prosperity of Big Data and 5G network technology brings new …

A Conflict-aware Dynamic Relocation Scheme of AGVs in Warehouse Logistics

M Huang, Y Zhou - 2023 IEEE International Conference on …, 2023 - ieeexplore.ieee.org
Automated guided vehicles (AGVs) have gradually become important for transferring goods
in warehouse logistics. To improve efficiency, various scheduling and routing methods have …