most cited5G UE and Network Asset Administration Shells for the Integration of 5G and Industry 4.0 Systems

7 citations · 15 across the 16 of their papers we have counts for

collaborators

24 papers

cs.NI2026

Execution Timing Control for Deterministic Task Offloading in the IoT-Edge-Cloud Continuum

Keyvan Aghababaiyan, Baldomero Coll-Perales, Javier Gozalvez

Latency-critical IoT applications, such as autonomous mobility and industrial automation, require deterministic guarantees to ensure that tasks are completed within strict deadline…

cs.NI2026

How the Fusion of Onboard Sensors and V2X Data can Improve (or not) the Cooperative Perception of Connected Automated Vehicles

Amir Mohammadisarab, Miguel Sepulcre, Luca Lusvarghi +1

Automated vehicles rely on onboard sensors to perceive their surroundings and navigate autonomously. However, sensor performance may degrade under adverse weather conditions or whe…

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.NI20262 cited

Latency-Sensitive 5G RAN Slicing for Deterministic Aperiodic Traffic in Smart Manufacturing

M. Carmen Lucas-Estañ, Jan García-Morales, Javier Gozalvez

5G and beyond networks will support the digitalization of smart manufacturing thanks to their capacity to simultaneously serve different types of traffic with distinct QoS requirem…

cs.NI2026

Importance of Intent-Sharing for V2X-based Maneuver Coordination

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

This paper examines the critical role of intent-sharing in enabling effective maneuver coordination for connected and automated vehicles (CAVs). Successful maneuver coordinations r…

cs.NI20261 cited

FORESEE: A Cooperative Lane Change Model for Connected and Automated Driving

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

This paper presents FORESEE, a novel cooperative lane change model for connected and automated driving. FORESEE leverages Vehicle-to-Everything (V2X) data to anticipate traffic con…