| Motion planning for autonomous driving: The state of the art and future perspectives S Teng, X Hu, P Deng, B Li, Y Li, Y Ai, D Yang, L Li, Z Xuanyuan, F Zhu, ... IEEE Transactions on Intelligent Vehicles 8 (6), 3692-3711, 2023 | 404 | 2023 |
| Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles X Hu, L Chen, B Tang, D Cao, H He Mechanical systems and signal processing 100, 482-500, 2018 | 368 | 2018 |
| Parallel planning: A new motion planning framework for autonomous driving L Chen, X Hu, W Tian, H Wang, D Cao, FY Wang IEEE/CAA Journal of Automatica Sinica 6 (1), 236-246, 2018 | 137 | 2018 |
| Hierarchical interpretable imitation learning for end-to-end autonomous driving S Teng, L Chen, Y Ai, Y Zhou, Z Xuanyuan, X Hu IEEE Transactions on Intelligent Vehicles 8 (1), 673-683, 2022 | 103 | 2022 |
| Conditional DQN-based motion planning with fuzzy logic for autonomous driving L Chen, X Hu, B Tang, Y Cheng IEEE Transactions on Intelligent Transportation Systems 23 (4), 2966-2977, 2020 | 102 | 2020 |
| Turn signal detection during nighttime by CNN detector and perceptual hashing tracking L Chen, X Hu, T Xu, H Kuang, Q Li IEEE Transactions on Intelligent Transportation Systems 18 (12), 3303-3314, 2017 | 90 | 2017 |
| How simulation helps autonomous driving: A survey of sim2real, digital twins, and parallel intelligence X Hu, S Li, T Huang, B Tang, R Huai, L Chen IEEE Transactions on Intelligent Vehicles, 2023 | 69 | 2023 |
| FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion S Teng, L Li, Y Li, X Hu, L Li, Y Ai, L Chen Mechanical Systems and Signal Processing 208, 111051, 2024 | 57 | 2024 |
| Learning a deep cascaded neural network for multiple motion commands prediction in autonomous driving X Hu, B Tang, L Chen, S Song, X Tong IEEE Transactions on Intelligent Transportation Systems 22 (12), 7585-7596, 2020 | 36 | 2020 |
| Yunfeng Ai, Dongsheng Yang, Lingxi Li, Zhe Xuanyuan, Fenghua Zhu, et al. Motion planning for autonomous driving: The state of the art and future perspectives S Teng, X Hu, P Deng, B Li, Y Li IEEE Transactions on Intelligent Vehicles 2, 2023 | 31 | 2023 |
| A novel approach for crowd video monitoring of subway platforms X Hu, H Zheng, W Wang, X Li Optik 124 (22), 5301-5306, 2013 | 29 | 2013 |
| Learning a deep motion planning model for autonomous driving S Song, X Hu, J Yu, L Bai, L Chen 2018 IEEE Intelligent Vehicles Symposium (IV), 1137-1142, 2018 | 26 | 2018 |
| Dense crowd counting based on perspective weight model using a fisheye camera X Hu, H Zheng, Y Chen, L Chen Optik 126 (1), 123-130, 2015 | 23 | 2015 |
| Parallel motion planning: Learning a deep planning model against emergencies L Chen, X Hu, B Tang, D Cao IEEE Intelligent Transportation Systems Magazine 11 (1), 36-41, 2018 | 19 | 2018 |
| A learning based approach for social force model parameter estimation Z Wan, X Hu, H He, Y Guo 2017 International Joint Conference on Neural Networks (IJCNN), 4058-4064, 2017 | 18 | 2017 |
| Learning dynamic graph for overtaking strategy in autonomous driving X Hu, Y Liu, B Tang, J Yan, L Chen IEEE Transactions on Intelligent Transportation Systems 24 (11), 11921-11933, 2023 | 13 | 2023 |
| Crowd Motion Estimation Using a Fisheye Camera X HU, H ZHENG, L GUO, R XIONG Geomatics and Information Science of Wuhan University 42 (4), 537-542, 2017 | 7 | 2017 |
| A novel object detection approach for satellite imagery based on danger theory H Zheng, X Hu, X Si, W Yang 2008 First International Conference on Intelligent Networks and Intelligent …, 2008 | 6 | 2008 |
| Path planning for autonomous driving: The state of the art and perspectives S Teng, P Deng, Y Li, B Li, X Hu, Z Xuanyuan, L Chen, Y Ai, L Li, ... arXiv preprint arXiv 2303, 2023 | 5 | 2023 |
| Abnormal crowd behavior detection and location based on spatial-temporal cube X HU, J YU, C DENG, S SONG, Q CHEN Geomatics and Information Science of Wuhan University 44 (10), 1530-1537, 2019 | 5 | 2019 |
