| On the impact of cooperative autonomous vehicles in improving freeway merging: a modified intelligent driver model-based approach M Zhou, X Qu, S Jin IEEE Transactions on Intelligent Transportation Systems 18 (6), 1422-1428, 2016 | 292 | 2016 |
| A recurrent neural network based microscopic car following model to predict traffic oscillation M Zhou, X Qu, X Li Transportation research part C: emerging technologies 84, 245-264, 2017 | 279 | 2017 |
| Jointly Dampening Traffic Oscillations and Improving Energy Consumption with Electric, Connected and Automated Vehicles: A Reinforcement Learning Based Approach X Qu, Y Yu, M Zhou, CT Lin, X Wang Applied Energy 257, 114030, 2020 | 231 | 2020 |
| Development of an Efficient Driving Strategy for Connected and Automated Vehicles at Signalized Intersections: A Reinforcement Learning Approach M Zhou, Y Yu, X Qu IEEE Transactions on Intelligent Transportation Systems 21 (1), 433-443, 2020 | 231 | 2020 |
| Improving efficiency at highway T-junctions with connected and automated vehicles M Zhou, X Qu, W Qi Transportmetrica A: transport science 17 (1), 107-123, 2021 | 11 | 2021 |
| Microscopic car-following model for autonomous vehicles using reinforcement learning M Zhou, X Qu Symposium on Innovations in Traffic Flow Theory and Characteristics and TFT …, 2016 | 7 | 2016 |
| Modeling the Impact of Connected and Automated Vehicles on Highway Operations M Zhou Griffith University, 2018 | 2 | 2018 |
| 面向应用的深度神经网络图说 孙澄宇， 周沫凡， 胡苇 时代建筑, 50-55, 2018 | | 2018 |
Xiaobo Qu (曲小波)Chair Professor of Intelligent TransportationVerified email at tsinghua.edu.cn
