activity
20242026
collaborators

6 papers

cs.CV2026

4D Radar Meets LiDAR and Camera: Cooperative Perception under Adverse Weather

Melih Yazgan, Iramm Hamdard, Qiyuan Wu +1

Cooperative perception is important for autonomous driving but remains fragile when cameras and LiDAR degrade in adverse weather. We address this challenge by integrating 4D imagin…

cs.CV2025

SlimComm: Doppler-Guided Sparse Queries for Bandwidth-Efficient Cooperative 3-D Perception

Melih Yazgan, Qiyuan Wu, Iramm Hamdard +2

Collaborative perception allows connected autonomous vehicles (CAVs) to overcome occlusion and limited sensor range by sharing intermediate features. Yet transmitting dense Bird's-…

cs.CV2025

EffiComm: Bandwidth Efficient Multi Agent Communication

Melih Yazgan, Allen Xavier Arasan, J. Marius Zöllner

Collaborative perception allows connected vehicles to exchange sensor information and overcome each vehicle's blind spots. Yet transmitting raw point clouds or full feature maps ov…

cs.CV2025

Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectors

Svetlana Pavlitska, Jamie Robb, Nikolai Polley +2

Realistic adversarial attacks on various camera-based perception tasks of autonomous vehicles have been successfully demonstrated so far. However, only a few works considered attac…

cs.RO2025

Centralized Decision-Making for Platooning By Using SPaT-Driven Reference Speeds

Melih Yazgan, Süleyman Tatar, J. Marius Zöllner

This paper introduces a centralized approach for fuel-efficient urban platooning by leveraging real-time Vehicle- to-Everything (V2X) communication and Signal Phase and Timing (SPa…

cs.RO2024

Empowering Autonomous Shuttles with Next-Generation Infrastructure

Sven Ochs, Melih Yazgan, Rupert Polley +9

As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how peo…