8 papers
How Roadside Units Enhance Intersection Safety? Cooperative Autonomous Driving System Design and A Proof of Concept
Taoyuan Yu, Kui Wang, Zongdian Li +3
Intersections remain one of the most hazardous locations in urban road networks, where heterogeneous traffic participants and limited visibility frequently lead to severe traffic c…
Diffusion Models for Solving Inverse Problems via Posterior Sampling with Piecewise Guidance
Saeed Mohseni-Sehdeh, Walid Saad, Kei Sakaguchi +1
Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When…
Transformer Architecture with Minimal Inference Latency for Multi-Modal Wireless Networks
Minsu Kim, Walid Saad, Kui Wang +3
Next-generation wireless networks are expected to leverage multi-modal data sources to execute various wireless communication tasks such as beamforming and blockage prediction with…
Predicting Networks Before They Happen: Experimentation on a Real-Time V2X Digital Twin
Roberto Pegurri, Habu Shintaro, Francesco Linsalata +6
Emerging safety-critical Vehicle-to-Everything (V2X) applications require networks to proactively adapt to rapid environmental changes rather than merely reacting to them. While Ne…
Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
Taoyuan Yu, Kui Wang, Zongdian Li +3
Unsignalized intersections pose safety and efficiency challenges due to complex traffic flows and blind spots. In this paper, a digital twin (DT)-based cooperative driving system w…
Multi-Agent Reinforcement Learning-based Cooperative Autonomous Driving in Smart Intersections
Taoyuan Yu, Kui Wang, Zongdian Li +2
Unsignalized intersections pose significant safety and efficiency challenges due to complex traffic flows. This paper proposes a novel roadside unit (RSU)-centric cooperative drivi…