469 citations · 1.3k across the 28 of their papers we have counts for
6 papers · 1 filter
VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness
Xuan Cai, Zhiyong Cui, Xuesong Bai +4
Autonomous vehicles (AVs) face significant threats to their safe operation in complex traffic environments. Adversarial training has emerged as an effective method of enabling AVs…
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…
Two-Stream Multi-Channel Convolutional Neural Network (TM-CNN) for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact
Ruimin Ke, Wan Li, Zhiyong Cui +1
Traffic speed prediction is a critically important component of intelligent transportation systems (ITS). Recently, with the rapid development of deep learning and transportation d…
Safe, Efficient, and Comfortable Velocity Control based on Reinforcement Learning for Autonomous Driving
Meixin Zhu, Yinhai Wang, Ziyuan Pu +3
A model used for velocity control during car following was proposed based on deep reinforcement learning (RL). To fulfil the multi-objectives of car following, a reward function re…
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
Zhiyong Cui, Kristian Henrickson, Ruimin Ke +2
Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due to the time-varying traffic patterns and the complicated spatial dependencies on ro…
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…