397 citations · 804 across the 16 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…