Control engineering, Vehicle dynamics, Control theory, Energy management and Powertrain are his primary areas of study. The Control engineering study combines topics in areas such as Obstacle avoidance, Motion planning, Trajectory and Automation. His Vehicle dynamics research includes themes of Control system, Control theory, Platoon and Torque.
His is doing research in Robustness and Feed forward, both of which are found in Control theory. His studies in Energy management integrate themes in fields like Intelligent transportation system, Automotive engineering, Internal combustion engine, Optimal control and Advanced driver assistance systems. Dongpu Cao has included themes like Electric vehicle and Automotive industry in his Powertrain study.
His main research concerns Artificial intelligence, Control theory, Automotive engineering, Vehicle dynamics and Control engineering. His work deals with themes such as Machine learning, Computer vision and Pattern recognition, which intersect with Artificial intelligence. His research in Control theory intersects with topics in Electric vehicle and Model predictive control.
His Automotive engineering research incorporates themes from Powertrain and Energy management. His Vehicle dynamics research is multidisciplinary, incorporating elements of Control system and Nonlinear system. His Control engineering research incorporates elements of Automation, Control and Reinforcement learning.
Dongpu Cao mainly investigates Artificial intelligence, Control, Reinforcement learning, Deep learning and Computer vision. His research integrates issues of Machine learning and Pattern recognition in his study of Artificial intelligence. His study looks at the intersection of Control and topics like Operations research with Trajectory.
His Reinforcement learning research includes elements of Intersection, Control theory, Real-time computing, Overtaking and Task analysis. His work carried out in the field of Deep learning brings together such families of science as Artificial neural network, Recurrent neural network and State. Dongpu Cao combines subjects such as Visualization and Odometry with his study of Computer vision.
His primary areas of study are Artificial intelligence, Control, Deep learning, Reinforcement learning and Trajectory. His Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition. His Control research is multidisciplinary, relying on both Advanced driver assistance systems, Key and Operations research.
His Advanced driver assistance systems research is multidisciplinary, incorporating perspectives in Control system and Automation. He works mostly in the field of Trajectory, limiting it down to concerns involving Motion planning and, occasionally, Tracking, CarSim and Obstacle avoidance. Within one scientific family, Dongpu Cao focuses on topics pertaining to Shortest path problem under Collision avoidance, and may sometimes address concerns connected to Control theory.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective
Clara Marina Martinez;Xiaosong Hu;Dongpu Cao;Efstathios Velenis.
IEEE Transactions on Vehicular Technology (2017)
Stability and Scalability of Homogeneous Vehicular Platoon: Study on the Influence of Information Flow Topologies
Yang Zheng;Shengbo Eben Li;Jianqiang Wang;Dongpu Cao.
IEEE Transactions on Intelligent Transportation Systems (2016)
Editors’ perspectives: road vehicle suspension design, dynamics, and control
Dongpu Cao;Xubin Song;Mehdi Ahmadian.
Vehicle System Dynamics (2011)
Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling
Xiaosong Hu;Jiuchun Jiang;Dongpu Cao;Bo Egardt.
IEEE Transactions on Industrial Electronics (2016)
Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey
Clara Marina Martinez;Mira Heucke;Fei-Yue Wang;Bo Gao.
IEEE Transactions on Intelligent Transportation Systems (2018)
Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles
Xiaohui Li;Zhenping Sun;Dongpu Cao;Daxue Liu.
Mechanical Systems and Signal Processing (2017)
Integrated Optimization of Battery Sizing, Charging, and Power Management in Plug-In Hybrid Electric Vehicles
Xiaosong Hu;Scott J. Moura;Nikolce Murgovski;Bo Egardt.
IEEE Transactions on Control Systems and Technology (2016)
Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle
Teng Liu;Xiaosong Hu;Shengbo Eben Li;Dongpu Cao.
IEEE-ASME Transactions on Mechatronics (2017)
A theoretical and computational study of lithium-ion battery thermal management for electric vehicles using heat pipes
Angelo Greco;Dongpu Cao;Xi Jiang;Hong Yang.
Journal of Power Sources (2014)
Real-Time Trajectory Planning for Autonomous Urban Driving: Framework, Algorithms, and Verifications
Xiaohui Li;Zhenping Sun;Dongpu Cao;Zhen He.
IEEE-ASME Transactions on Mechatronics (2016)
Profile was last updated on December 6th, 2021.
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