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Luyao Zhang - IEEE Xplore Author Profile
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Luyao Zhang

Publications
5
Citations
38
Publications by Year
20222024
Co-Authors:
Show All Co-Authors (11)
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Luyao Zhang

Affiliation

Delft Center for Systems and Control, Delft University of Technology, The Netherlands

Publication Topics

Biography

Luyao Zhang received the B.S. degree in electronic information engineering, in 2020, from the College of Electronic and Information Engineering, Hebei University, Baoding, China, where she is currently working toward the M.S. degree in information and communication engineering.,Her research interests include signal processing and image processing.(Based on document published on 25 October 2023).
Publications
5
Citations
38
Publications by Year
20222024
Co-Authors:
Show All Co-Authors (11)
Author's Published Works

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An Efficient Risk-aware Branch MPC for Automated Driving that is Robust to Uncertain Vehicle Behaviors

Luyao Zhang;Georgios Pantazis;Shaohang Han;Sergio Grammatico

2024 IEEE 63rd Conference on Decision and Control (CDC)
Year: 2024 | Conference Paper |
One of the critical challenges in automated driving is ensuring safety of automated vehicles despite the unknown behavior of the other vehicles. Although motion prediction modules are able to generate a probability distribution associated with various behavior modes, their probabilistic estimates are often inaccurate, thus leading to a possibly unsafe motion plan. To overcome this challenge, we pr...Show More

An Efficient Risk-aware Branch MPC for Automated Driving that is Robust to Uncertain Vehicle Behaviors

Luyao Zhang;Georgios Pantazis;Shaohang Han;Sergio Grammatico

Year: 2024 | Conference Paper |

Automated Lane Merging via Game Theory and Branch Model Predictive Control

Luyao Zhang;Shaohang Han;Sergio Grammatico

IEEE Transactions on Control Systems Technology
Year: 2024 | Early Access Article |
We propose an integrated behavior and motion planning framework for the lane-merging problem. The behavior planner combines search-based planning with game theory to model vehicle interactions and plan multivehicle trajectories. Inspired by human drivers, we model the lane-merging problem as a gap selection process and determine the appropriate gap by solving a matrix game. Moreover, we introduce ...Show More

Automated Lane Merging via Game Theory and Branch Model Predictive Control

Luyao Zhang;Shaohang Han;Sergio Grammatico

Year: 2024 | Early Access Article |

An Efficient Game-Theoretic Planner for Automated Lane Merging with Multi-Modal Behavior Understanding

Luyao Zhang;Shaohang Han;Sergio Grammatico

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In this paper, we propose a novel behavior planner that combines game theory with search-based planning for automated lane merging. Specifically, inspired by human drivers, we model the interaction between vehicles as a gap selection process. To overcome the challenge of multi-modal behavior exhibited by the surrounding vehicles, we formulate the trajectory selection as a matrix game and compute a...Show More

An Efficient Game-Theoretic Planner for Automated Lane Merging with Multi-Modal Behavior Understanding

Luyao Zhang;Shaohang Han;Sergio Grammatico

Year: 2023 | Conference Paper |

MFAENet: A Multiscale Feature Adaptive Enhancement Network for SAR Image Despeckling

Shuaiqi Liu;Luyao Zhang;Shikang Tian;Qi Hu;Bing Li;Yudong Zhang

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2023 | Volume: 16 | Journal Article |
Cited by: Papers (1)
The existence of speckles in synthetic aperture radar (SAR) images affects its subsequent application in computer vision tasks, so the research of speckle suppression plays a very important role. Convolutional neural networks based speckle suppression algorithms cannot reach a good balance between despeckling effect and structure detail preservation. Considering these issues, a multiscale feature ...Show More

MFAENet: A Multiscale Feature Adaptive Enhancement Network for SAR Image Despeckling

Shuaiqi Liu;Luyao Zhang;Shikang Tian;Qi Hu;Bing Li;Yudong Zhang

Year: 2023 | Volume: 16 | Journal Article |

MRDDANet: A Multiscale Residual Dense Dual Attention Network for SAR Image Denoising

Shuaiqi Liu;Yu Lei;Luyao Zhang;Bing Li;Weiming Hu;Yu-Dong Zhang

IEEE Transactions on Geoscience and Remote Sensing
Year: 2022 | Volume: 60 | Journal Article |
Cited by: Papers (36)
Synthetic aperture radar (SAR), due to its inherent characteristics, will produce speckle noise, which results in the deterioration of image quality, so the removal of speckle in SAR image is very important for the subsequent high-level image processing. In order to balance the relationship between denoising and texture preservation, we propose a multiscale residual dense dual attention network (M...Show More

MRDDANet: A Multiscale Residual Dense Dual Attention Network for SAR Image Denoising

Shuaiqi Liu;Yu Lei;Luyao Zhang;Bing Li;Weiming Hu;Yu-Dong Zhang

Year: 2022 | Volume: 60 | Journal Article |

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