445 citations · 793 across the 15 of their papers we have counts for
16 papers
Uncertainty-aware Traffic Prediction under Missing Data
Hao Mei, Junxian Li, Zhiming Liang +3
Traffic prediction is a crucial topic because of its broad scope of applications in the transportation domain. Recently, various studies have achieved promising results. However, m…
Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank
Zhanyu Liu, Guanjie Zheng, Yanwei Yu
Traffic forecasting is a critical service in Intelligent Transportation Systems (ITS). Utilizing deep models to tackle this task relies heavily on data from traffic sensors or vehi…
FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph
Zhanyu Liu, Chumeng Liang, Guanjie Zheng +1
This paper proposes the fine-grained traffic prediction task (e.g. interval between data points is 1 minute), which is essential to traffic-related downstream applications. Under t…
HMES: A Scalable Human Mobility and Epidemic Simulation System with Fast Intervention Modeling
Haoyu Geng, Guanjie Zheng, Zhengqing Han +2
Recently, the world has witnessed the most severe pandemic (COVID-19) in this century. Studies on epidemic prediction and simulation have received increasing attention. However, th…
CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulation
Chumeng Liang, Zherui Huang, Yicheng Liu +7
Traffic simulation provides interactive data for the optimization of traffic control policies. However, existing traffic simulators are limited by their lack of scalability and sho…
MedAttacker: Exploring Black-Box Adversarial Attacks on Risk Prediction Models in Healthcare
Muchao Ye, Junyu Luo, Guanjie Zheng +3
Deep neural networks (DNNs) have been broadly adopted in health risk prediction to provide healthcare diagnoses and treatments. To evaluate their robustness, existing research cond…
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…
Objective-aware Traffic Simulation via Inverse Reinforcement Learning
Guanjie Zheng, Hanyang Liu, Kai Xu +1
Traffic simulators act as an essential component in the operating and planning of transportation systems. Conventional traffic simulators usually employ a calibrated physical car-f…
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…
Targeted Source Detection for Environmental Data
Guanjie Zheng, Mengqi Liu, Tao Wen +4
In the face of growing needs for water and energy, a fundamental understanding of the environmental impacts of human activities becomes critical for managing water and energy resou…
Learning Phase Competition for Traffic Signal Control
Guanjie Zheng, Yuanhao Xiong, Xinshi Zang +6
Increasingly available city data and advanced learning techniques have empowered people to improve the efficiency of our city functions. Among them, improving the urban transportat…
Diagnosing Reinforcement Learning for Traffic Signal Control
Guanjie Zheng, Xinshi Zang, Nan Xu +5
With the increasing availability of traffic data and advance of deep reinforcement learning techniques, there is an emerging trend of employing reinforcement learning (RL) for traf…
CoLight: Learning Network-level Cooperation for Traffic Signal Control
Hua Wei, Nan Xu, Huichu Zhang +7
Cooperation among the traffic signals enables vehicles to move through intersections more quickly. Conventional transportation approaches implement cooperation by pre-calculating t…
A Survey on Traffic Signal Control Methods
Hua Wei, Guanjie Zheng, Vikash Gayah +1
Traffic signal control is an important and challenging real-world problem, which aims to minimize the travel time of vehicles by coordinating their movements at the road intersecti…
Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction
Huaxiu Yao, Xianfeng Tang, Hua Wei +2
Traffic prediction has drawn increasing attention in AI research field due to the increasing availability of large-scale traffic data and its importance in the real world. For exam…