most citedDirect-V2X Support with 5G Network-based Communications: Performance, Challenges and Solutions

13 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NI2026

Fusion or Confusion? Potential and Challenges in Fusion of Onboard Sensors and V2X Data in Cooperative Perception

Amir Mohammadisarab, Miguel Sepulcre, Luca Lusvarghi +5

Connected Automated Vehicles (CAVs) utilize their onboard sensors to perceive the environment. The perception range and accuracy can be affected by adverse weather or non-line-of-s…

cs.NI2026

Multi-Target Maneuver Coordinations: Unlocking Coordination Opportunities in Connected Automated Driving

Rafael Molina-Masegosa, Sergei S. Avedisov, Miguel Sepulcre +3

Maneuver coordination is a key enabler of connected and automated driving, allowing vehicles to negotiate and execute maneuvers that would otherwise be difficult, inefficient or un…

cs.RO2026

FleetAgent: Teleoperation Assistant for Autonomous Fleets via Vectorized V2N Messages

Juntong Peng, Qi Chen, Deyuan Qu +3

Large-scale autonomous fleets rely on teleoperation to resolve rare failures, yet streaming raw sensor data from many vehicles is costly, and remote operators can only monitor a li…

cs.NI202613 cited

Direct-V2X Support with 5G Network-based Communications: Performance, Challenges and Solutions

M. C. Lucas-Estañ, B. Coll-Perales, T. Shimizu +5

This study analyzes the feasibility of supporting critical V2X services using 5G network-based Vehicle-to-Network-to-Vehicle (V2N2V) communications. The study evaluates the end-to-…

cs.RO2026

CooperDrive: Enhancing Driving Decisions Through Cooperative Perception

Deyuan Qu, Qi Chen, Takayuki Shimizu +1

Autonomous vehicles equipped with robust onboard perception, localization, and planning still face limitations in occlusion and non-line-of-sight (NLOS) scenarios, where delayed re…