| Envisioning the future of transportation: Inspiration of ChatGPT and large models X Qu, H Lin, Y Liu Communications in Transportation Research 3, 100103, 2023 | 68 | 2023 |
| How generative adversarial networks promote the development of intelligent transportation systems: A survey H Lin, Y Liu, S Li, X Qu IEEE/CAA journal of automatica sinica, 2023 | 48 | 2023 |
| Deep demand prediction: An enhanced conformer model with cold-start adaptation for origin–destination ride-hailing demand prediction H Lin, Y He, Y Liu, K Gao, X Qu IEEE Intelligent Transportation Systems Magazine, 2023 | 19 | 2023 |
| Enhancing State Representation in Multi-Agent Reinforcement Learning for Platoon-Following Models H Lin, C Lyu, Y He, Y Liu, K Gao, X Qu IEEE Transactions on Vehicular Technology, 2024 | 9 | 2024 |
| Applying masked language model for transport mode choice behavior prediction Y Yang, W Zhang, H Lin, Y Liu, X Qu Transportation Research Part A: Policy and Practice 184, 104074, 2024 | 4 | 2024 |
| AEFusion: An Attention-Based Ensemble Learning Approach for BEV Fusion Perception in Autonomous Modular Buses H Lin, S Ming, Y Liu, X Qu IEEE Transactions on Intelligent Vehicles, 2024 | 2 | 2024 |
| A High-Precision Calibration and Evaluation Method Based on Binocular Cameras and LiDAR for Intelligent Vehicles H Lin, L Wang, X Qu IEEE Transactions on Vehicular Technology, 2025 | | 2025 |
| Big Data-Driven Advancements and Future Directions in Vehicle Perception Technologies: From Autonomous Driving to Modular Buses H Lin, Y Liu, L Wang, X Qu IEEE Transactions on Big Data, 2025 | | 2025 |
