243 citations · 314 across the 7 of their papers we have counts for
4 papers · 1 filter
Learning to Route via Theory-Guided Residual Network
Chang Liu, Guanjie Zheng, Zhenhui Li
The heavy traffic and related issues have always been concerns for modern cities. With the help of deep learning and reinforcement learning, people have proposed various policies t…
Learning to Simulate on Sparse Trajectory Data
Hua Wei, Chacha Chen, Chang Liu +2
Simulation of the real-world traffic can be used to help validate the transportation policies. A good simulator means the simulated traffic is similar to real-world traffic, which…
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning
Chang Liu, Huichu Zhang, Weinan Zhang +2
The heavy traffic congestion problem has always been a concern for modern cities. To alleviate traffic congestion, researchers use reinforcement learning (RL) to develop better tra…
ALCNN: Attention-based Model for Fine-grained Demand Inference of Dock-less Shared Bike in New Cities
Chang Liu, Yanan Xu, Yanmin Zhu
In recent years, dock-less shared bikes have been widely spread across many cities in China and facilitate people's lives. However, at the same time, it also raises many problems a…