基本信息

王涣杰，工学博士，北京工业大学机械与能源工程学院，学术学位硕士生导师，专业学位硕士生导师。2021年博士毕业于北京理工大学，曾赴美国加州大学伯克利分校开展为期两年的访问学习。主要从事与智能车辆和移动机器人相关的理论、应用技术以及人工智能等交叉领域前沿研究。担任第六届、第七届及第八届IEEE国际无人系统大会专题主席，中国汽车工程学会年会评审专家，以及IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Vehicular Technology,IEEE Transactions on Transportation Electrification,Engineering Applications of Artificial Intelligence, IEEE/ASME Transactions on Mechatronics,IEEE Sensors Journal,IEEE Transactions on Intelligent Vehicles, CAAI Transactions on Intelligence Technology等SCI期刊和领域顶级会议的审稿人。

研究方向

自主智能系统，智能决策理论与技术，环境感知与导航控制，机器学习理论与技术

主要科研项目

1.国家自然科学基金青年项目，数据与模型双驱动的自动驾驶可信决策方法研究，主持

2.北京市教委科研计划科技一般项目，自动驾驶车辆可信赖系统建模及关键技术研究，主持

3.中国博士后科学基金面上项目，数据与知识协同驱动的可信赖自动驾驶系统建模研究，主持

4.北京市博士后基金项目，基于可解释表征与不确定量化的自动驾驶可信建模研究，主持

5.国家重点研发计划重点专项，固体发动机及DT智能生产线构建的关键技术研究与应用，参与

代表性研究成果

1.H. Wang, H. Liu, W. Wang, and L. Sun. On Trustworthy Decision-Making Process ofHumanDrivers from the View of Perceptual Uncertainty Reduction [J]. IEEE Transactions on Intelligent Transportation Systems, 2024.（SCI）

2.H. Wang, W. Wang, S. Yuan, X. Li, and L. Sun. On Social Interactions of Merging Behaviors at Highway On-Ramps in Congested Traffic [J]. IEEE Transactions on Intelligent Transportation Systems, 2022.（SCI）

3.H. Wang, H. Gao, S. Yuan, H. Zhao, K. Wang, X. Wang, K. Li, and D. Li. Interpretable Decision-Making for Autonomous Vehicles at Highway On-Ramps with Latent Space Reinforcement Learning [J]. IEEE Transactions on Vehicular Technology, 2021.（SCI）

4.H. Wang, W. Wang, S. Yuan, and X. Li. Uncovering Interpretable Internal States of Merging Tasks at Highway On-Ramps for Autonomous Driving Decision-Making [J]. IEEE Transactions on Automation Science and Engineering, 2022.（SCI）

5. H. Liu, C. Wu,H. Wang*. Real Time Object Detection Using LiDAR and Camera Fusion for Autonomous Driving [J]. Scientific Reports, 2023.（SCI）

6.H. Wang, S. Yuan, M. Guo, C. Chan, X. Li, and W. Lan. Tactical driving decisions of unmanned ground vehicles in complex highway environments: A deep reinforcement learning approach [J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2021.（SCI）

7.H. Wang, S. Yuan, M. Guo, X. Li, and W. Lan. A Deep Reinforcement Learning-Based Approach for Autonomous Driving in Highway On-Ramp Merge [J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 2021.（SCI）

8.H. Wang, J. Hu, H. Liu, H. Liu. On uncertainty quantification impact for autonomous driving decisions at intersections [C]. 2024 7th IEEE International Conference on Unmanned Systems (ICUS). IEEE, 2024.（EI）

9. H. Liu, Y. Tang,H. Wang*. Improved Monte CarloLocalizationBased on Probability Density Maps for Autonomous Mobile Robots [C]. 2023 6th IEEE International Conference on Unmanned Systems (ICUS). IEEE, 2023.（EI）

10. M. Li, H. Liu,H. Wang*, and M. Xia. Trustworthy dynamic object tracking using deep reinforcement learning with the self-attention mechanism [C]. 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE). IEEE, 2023.（EI）

招生方向

欢迎具有机械、车辆、计算机、自动化、数学等相关专业背景的学生申请推免或报考研究生