papers

Publications (11)

cs.LG2026

Tracking Large-scale Shared Bikes with Inertial Motion Learning in GNSS Blocked Environments

Feng Liu, Kejia Li, Zhiwei Yang +5

Although Global Navigation Satellite Systems (GNSS) provide a general solution for bike tracking outdoors, there still exist complex riding environments where only inertial navigat…

cs.AI2024

Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey

Ao Fu, Yi Zhou, Tao Zhou +5

World models and video generation are pivotal technologies in the domain of autonomous driving, each playing a critical role in enhancing the robustness and reliability of autonomo…

cs.MA2019

Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning

Minne Li, Zhiwei, Qin +7

A fundamental question in any peer-to-peer ridesharing system is how to, both effectively and efficiently, dispatch user's ride requests to the right driver in real time. Tradition…

cs.MA2019

Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching

Ming Zhou, Jiarui Jin, Weinan Zhang +6

Improving the efficiency of dispatching orders to vehicles is a research hotspot in online ride-hailing systems. Most of the existing solutions for order-dispatching are centralize…

eess.SP2020

Spatio-Temporal Hierarchical Adaptive Dispatching for Ridesharing Systems

Chang Liu, Jiahui Sun, Haiming Jin +7

Nowadays, ridesharing has become one of the most popular services offered by online ride-hailing platforms (e.g., Uber and Didi Chuxing). Existing ridesharing platforms adopt the s…

cs.LG2025

A Knowledge-Guided Cross-Modal Feature Fusion Model for Local Traffic Demand Prediction

Lingyu Zhang, Pengfei Xu, Guobin Wu +4

Traffic demand prediction plays a critical role in intelligent transportation systems. Existing traffic prediction models primarily rely on temporal traffic data, with limited effo…