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/专业学位硕士生导师。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，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, L. Sun. On Trustworthy Decision-Making Process of Human Drivers 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, 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, Y. Tang, J. Hu, H. Liu, W. Wang, C. Wei, C. Hu, W. Wang. Robust and High-Precision Point Cloud Registration Method Based on 3D-NDT Algorithm for Vehicle Localization [J]. IEEE Transactions on Vehicular Technology, 2025.（SCI）

[4]H. Wang, H. Gao, S. Yuan, H. Zhao, K. Wang, X. Wang, K. Li, 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）

[5]H. Wang, W. Wang, S. Yuan, 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）

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

[7]H. Wang, S. Yuan, M. Guo, C. Chan, X. Li, 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）

[8]H. Wang, S. Yuan, M. Guo, X. Li, 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）

[9]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）

[10]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）

[11]M. Li, H. Liu,H. Wang*, 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）

[12]基于激光雷达点云聚类的点云匹配定位方法、系统及产品[P].中国发明专利：ZL202310968359.7, 2025.

[13]一种基于激光雷达和相机数据融合的实时目标检测方法[P].中国发明专利：ZL202211177288.0, 2025.

[14]基于激光雷达的高精度鲁棒定位系统V1.0.软件著作权：2024SR1014427, 2024.

[15]支持不确定性量化的在线地图估计系统V1.0.软件著作权：2025SR0790637, 2025.

招生方向

欢迎具有机械、车辆、机器人、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！