397 citations · 804 across the 16 of their papers we have counts for
16 papers
MSCT: Addressing Time-Varying Confounding with Marginal Structural Causal Transformer for Counterfactual Post-Crash Traffic Prediction
Shuang Li, Ziyuan Pu, Nan Zhang +4
Traffic crashes profoundly impede traffic efficiency and pose economic challenges. Accurate prediction of post-crash traffic status provides essential information for evaluating tr…
Spatio-Temporal Graphical Counterfactuals: An Overview
Mingyu Kang, Duxin Chen, Ziyuan Pu +2
Counterfactual thinking is a crucial yet challenging topic for artificial intelligence to learn knowledge from data and ultimately improve performance for new scenarios. Many resea…
Revealing the CO2 emission reduction of ridesplitting and its determinants based on real-world data
Wenxiang Li, Yuanyuan Li, Ziyuan Pu +3
Ridesplitting, which is a form of pooled ridesourcing service, has great potential to alleviate the negative impacts of ridesourcing on the environment. However, most existing stud…
TransFollower: Long-Sequence Car-Following Trajectory Prediction through Transformer
Meixin Zhu, Simon S. Du, Xuesong Wang +4
Car-following refers to a control process in which the following vehicle (FV) tries to keep a safe distance between itself and the lead vehicle (LV) by adjusting its acceleration i…
Illumination and Temperature-Aware Multispectral Networks for Edge-Computing-Enabled Pedestrian Detection
Yifan Zhuang, Ziyuan Pu, Jia Hu +1
Accurate and efficient pedestrian detection is crucial for the intelligent transportation system regarding pedestrian safety and mobility, e.g., Advanced Driver Assistance Systems,…
Adversarial Diffusion Attacks on Graph-based Traffic Prediction Models
Lyuyi Zhu, Kairui Feng, Ziyuan Pu +1
Real-time traffic prediction models play a pivotal role in smart mobility systems and have been widely used in route guidance, emerging mobility services, and advanced traffic mana…
Learning dynamic and hierarchical traffic spatiotemporal features with Transformer
Haoyang Yan, Xiaolei Ma
Traffic forecasting is an indispensable part of Intelligent transportation systems (ITS), and long-term network-wide accurate traffic speed forecasting is one of the most challengi…
Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Forecasting Network-wide Traffic State with Missing Values
Zhiyong Cui, Ruimin Ke, Ziyuan Pu +1
Short-term traffic forecasting based on deep learning methods, especially recurrent neural networks (RNN), has received much attention in recent years. However, the potential of RN…
A Smart, Efficient, and Reliable Parking Surveillance System with Edge Artificial Intelligence on IoT Devices
Ruimin Ke, Yifan Zhuang, Ziyuan Pu +1
Cloud computing has been a main-stream computing service for years. Recently, with the rapid development in urbanization, massive video surveillance data are produced at an unprece…
Graph Markov Network for Traffic Forecasting with Missing Data
Zhiyong Cui, Longfei Lin, Ziyuan Pu +1
Traffic forecasting is a classical task for traffic management and it plays an important role in intelligent transportation systems. However, since traffic data are mostly collecte…
Road Surface Friction Prediction Using Long Short-Term Memory Neural Network Based on Historical Data
Ziyuan Pu, Shuo Wang, Chenglong Liu +2
Road surface friction significantly impacts traffic safety and mobility. A precise road surface friction prediction model can help to alleviate the influence of inclement road cond…
Mining Public Transit Ridership Flow and Origin-Destination Information from Wi-Fi and Bluetooth Sensing Data
Ziyuan Pu, Meixin Zhu, Zhiyong Cui +1
Transit ridership flow and origin-destination (O-D) information is essential for enhancing transit network design, optimizing transit route and improving service. The effectiveness…
Time-Aware Gated Recurrent Unit Networks for Road Surface Friction Prediction Using Historical Data
Ziyuan Pu, Zhiyong Cui, Shuo Wang +2
An accurate road surface friction prediction algorithm can enable intelligent transportation systems to share timely road surface condition to the public for increasing the safety…
Traffic Sign Detection and Recognition for Autonomous Driving in Virtual Simulation Environment
Meixin Zhu, Jingyun Hu, Ziyuan Pu +3
This study developed a traffic sign detection and recognition algorithm based on the RetinaNet. Two main aspects were revised to improve the detection of traffic signs: image cropp…
Personalized Context-Aware Multi-Modal Transportation Recommendation
Meixin Zhu, Jingyun Hu, Hao +3
This study proposes to find the most appropriate transport modes with awareness of user preferences (e.g., costs, times) and trip characteristics (e.g., purpose, distance). The wor…
Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction
Zhiyong Cui, Ruimin Ke, Ziyuan Pu +1
Short-term traffic forecasting based on deep learning methods, especially long short-term memory (LSTM) neural networks, has received much attention in recent years. However, the p…