Dr. Hao Yan
PhD in Electrical and Computer Engineering
Hao Yan earned his Ph.D. from Oakland University, where he began his doctoral studies in the Department of Electrical and Computer Engineering in January 2021. He received his M.S. in Electrical and Computer Engineering from The Ohio State University in 2018. His research interests include data-driven control systems that combine classical vehicle control algorithms with machine learning, computer vision, and pattern recognition. Documented research areas include autonomous parking, reinforcement learning and vehicle control.
Selected published work: “Trajectory State Model-based Reinforcement Learning for Truck-trailer Reverse Driving” (2024). Publication details and links are listed below.
Research & Publications
2 matched publications · Newest first
This list contains publications matched from publisher and author records. It may not include every publication.
Trajectory State Model-based Reinforcement Learning for Truck-trailer Reverse Driving
View PublicationStart here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
Recurrent Proximal Policy Optimization Based Tractor-Trailer Wheeled Robot Automatic Parking Algorithm
View PublicationStart here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
No publications match your search.