Boyang Wang
Orcid: 0000-0003-3613-8792Affiliations:
- Beijing Institute of Technology, College of Mechanical Engineering, China (PhD 2020)
- Peking University, Researcher with the Key Laboratory of Machine Perception, Beijing, China (2020-2022)
- CNRS-UM LIRMM, Interaction Digital Human Group, Montpellier, France (2017-2019)
According to our database1,
Boyang Wang
authored at least 16 papers
between 2018 and 2024.
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Bibliography
2024
Hierarchical Trajectory Planning Based on Adaptive Motion Primitives and Bilevel Corridor.
IEEE Trans. Veh. Technol., November, 2024
A Hierarchical Multi-Vehicle Coordinated Motion Planning Method Based on Interactive Spatio-Temporal Corridors.
IEEE Trans. Intell. Veh., January, 2024
TP-FRL: An Efficient and Adaptive Trajectory Prediction Method Based on the Rule and Learning-Based Frameworks Fusion.
IEEE Trans. Intell. Veh., January, 2024
A Slip Parameter Prediction Method Based on a Fusion Framework of Nonlinear Observer and Machine Learning.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024
Driving Behavior Primitive Optimization and Inter-Primitive Game Coordinated Control for Trajectory Tracking Applications.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024
Heterogeneous Vehicle Motion Planning Considering Multiple Differentiated Characteristic Constraints.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024
Coordinated Motion Planning for Heterogeneous Autonomous Vehicles Based on Driving Behavior Primitives.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2024
2023
Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework.
IEEE Trans. Intell. Transp. Syst., August, 2023
Isolating Trajectory Tracking From Motion Control: A Model Predictive Control and Robust Control Framework for Unmanned Ground Vehicles.
IEEE Robotics Autom. Lett., March, 2023
2021
Prediction of Pedestrian Spatiotemporal Risk Levels for Intelligent Vehicles: A Data-driven Approach.
CoRR, 2021
2020
Motion Primitives Representation, Extraction and Connection for Automated Vehicle Motion Planning Applications.
IEEE Trans. Intell. Transp. Syst., 2020
2019
Regeneration and Joining of the Learned Motion Primitives for Automated Vehicle Motion Planning Applications.
Proceedings of the 2019 IEEE Intelligent Vehicles Symposium, 2019
2018
Learning and Generalizing Motion Primitives From Driving Data for Path-Tracking Applications.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018
Development and Evaluation of Two Learning-Based Personalized Driver Models for Pure Pursuit Path-Tracking Behaviors.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018
Learning to Segment and Represent Motion Primitives from Driving Data for Motion Planning Applications.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018