ASVIC
Advancing Safe and Connected Smart Mobility
FEB, 28 2025 | 7 min.
Innovative Solutions for the Future of Autonomous and Intelligent Transportation
ASVIC (Secure Architecture for Intelligent and Connected Vehicles) is an innovative research initiative focused on enhancing the safety, efficiency, and connectivity of autonomous vehicles. As smart mobility continues to evolve, secure communication and reliable control systems are essential for improving traffic safety, reducing congestion, and optimizing vehicle coordination.
The project aims to develop a robust technological architecture that integrates advanced perception, localization, and communication technologies to improve vehicle awareness and decision-making in real-world environments. A key aspect of ASVIC is the implementation of cutting-edge 5G and 6G networks, ensuring ultra-low latency and high-speed data exchange between vehicles and infrastructure (V2V and V2I). By leveraging artificial intelligence (AI), edge computing, and cybersecurity innovations, ASVIC sets the foundation for a new era of intelligent, connected, and autonomous transportation.
Objectives
This research initiative is focused on developing an advanced and secure architecture for Level 4 autonomous vehicles, enabling their safe and efficient operation in controlled environments at speeds of up to 50 km/h. The project leverages cutting-edge technologies to enhance autonomous driving, communication, and cybersecurity, contributing to the evolution of smart mobility.
To achieve this, ASVIC focuses on key technological advancements:
- Development of a secure vehicle architecture, integrating perception, localization, navigation, and control technologies to ensure safe operations within defined Operational Design Domains (ODDs).
- Implementation of low-latency communication systems, utilizing 5G and 6G networks to facilitate real-time V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure) connectivity, crucial for enhanced road safety and traffic efficiency.
- AI-powered detection and automation, improving environment perception, obstacle detection, and system resilience, ensuring safe interactions between vehicles and infrastructure.
- Cybersecurity and data protection, ensuring the reliability and integrity of communications in connected autonomous systems.
- Validation of the developed technologies in laboratory environments, using simulation models to assess their feasibility before real-world implementation.
ASVIC sets the foundation for the future of smart mobility, leveraging cutting-edge AI, advanced communications, and automation technologies to create a safer, more connected, and efficient transportation ecosystem.
Our role
At Fivecomm, we specialize in advanced vehicular communications, playing a key role in ASVIC by designing and implementing a dedicated high-speed, low-latency communication architecture for autonomous Level 4 vehicles. Our expertise lies in enabling seamless and secure connectivity, which is essential for the next generation of intelligent mobility solutions.
Our work focuses on ensuring vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity, leveraging state-of-the-art 5G and 6G technologies to support real-time data exchange between autonomous vehicles and smart infrastructure. This enables precise coordination between road users, improving traffic flow efficiency and overall road safety.
Our research also focuses on optimizing edge computing capabilities, ensuring that vehicles can process critical data locally, reducing network congestion and improving response times in mission-critical scenarios.
Additionally, Fivecomm is working on cybersecurity solutions to protect vehicular communications from potential threats. By implementing secure network slicing techniques and encryption protocols, we ensure that autonomous vehicles operate in a resilient and tamper-proof digital environment. Our role in ASVIC is to push the boundaries of smart mobility communication, paving the way for safer, more connected, and more efficient autonomous transportation.
Project updates
Entregable 3.1 - Informe de requisitos y especificaciones de red de comunicaciones dedicada para vehículos inteligentes
The Deliverable 3.1 of the ASVIC project, developed within Activity 3, focuses on the definition of communication requirements and the design of the proposed network architecture to support the project’s autonomous vehicle use cases.
This document provides an in-depth analysis of the technological options for vehicle connectivity, evaluating both commercial and private 5G networks, as well as hybrid Multi-access Edge Computing (MEC) solutions that combine local and cloud-based resources.
A comprehensive review of the state of the art was conducted, including European research projects, academic studies, and cloud-based connectivity solutions (e.g., AWS Connected Vehicle, Private 5G, Wavelength). This analysis served as the foundation for identifying the most suitable communication architectures for autonomous and connected vehicles.
As part of this work, the key technical requirements for the network were defined, covering latency, reliability, capacity, and security, to ensure that the proposed solutions can meet the stringent demands of Level 4 autonomous driving.
Within this deliverable, Fivecomm carried out a detailed study of the communication infrastructure, identifying that the currently available network is based on LTE technology and therefore lacks 5G capabilities. Based on this analysis, two alternative network architectures were proposed:
- Commercial 5G network with hybrid MEC (local/cloud): A solution relying on operator-provided 5G connectivity complemented by edge computing nodes, allowing reduced latency and high reliability for teleoperation and video analytics.
- Private 5G network architecture: A fully controlled network deployed on-site, enabling strict control over Quality of Service (QoS), security, and local data processing, ideal for mission-critical applications such as autonomous driving and real-time perception.
This deliverable represents a key milestone in the ASVIC project, establishing the technical foundation for the upcoming validation phase, where the proposed network solutions will be implemented and tested in real environments.
Entregable 3.2 - Informe de comunicación e intercambio de información V2I
Deliverable 3.2 of the ASVIC project, developed within Activity 3, focuses on the analysis and validation of vehicle-to-infrastructure (V2I) communications in a real operational environment. The work aims to assess the suitability of current cellular networks to support advanced autonomous driving use cases, with particular emphasis on teleoperation and low-latency data exchange.
This deliverable combines extensive field measurement campaigns carried out by Renault with high-fidelity radio propagation simulations performed by Fivecomm using a ray-tracing–based proprietary simulator. The integration of real measurements and simulation enables a detailed characterization of coverage conditions, identification of critical areas, and validation of the communication performance along the autonomous vehicle route in Valladolid.
A key aspect of the work is the creation and calibration of a 3D digital twin of the test environment, allowing the simulation model to be progressively refined and aligned with real-world observations. The study demonstrates that, although the initial simulations tend to be conservative, the calibrated model provides a reliable and realistic representation of the radio channel.
Overall, this deliverable establishes a solid and validated basis for evaluating V2I communications in ASVIC, supporting subsequent analyses of latency and reliability and enabling informed decisions regarding communication infrastructure planning for Level 4 autonomous vehicles.
Entregable 3.3 - Informe de comunicación e intercambio de información V2V
Deliverable 3.3 of the ASVIC project addresses the study and evaluation of vehicle-to-vehicle (V2V) communications as a key enabler for cooperative and safe autonomous driving. Developed within Activity 3, this deliverable focuses on understanding the behavior of direct V2V links under realistic conditions and on providing validated models for subsequent simulation and system-level evaluation.
The work includes an extensive experimental campaign using Cohda Wireless equipment, covering multiple propagation scenarios such as line-of-sight (LoS), non-line-of-sight (NLoS), and obstructed line-of-sight (OLoS). These measurements allow the characterization of latency, packet error rate, and link robustness as a function of distance, geometry, and transmission parameters.
Based on the experimental results, a calibrated physical-layer abstraction model was developed, enabling realistic simulation of V2V communications within the ASVIC framework. This model serves as a bridge between real-world measurements and large-scale simulation, ensuring that the evaluated scenarios reflect actual radio behavior.
In addition, the deliverable proposes a preliminary deployment strategy for Road-Side Units (RSUs) in the Valladolid test environment, considering different performance targets and modulation schemes. This work provides essential input for the design of cooperative communication architectures and supports the validation of V2V technologies for autonomous driving in controlled environments.
Financing and partners
ASVIC is a collaborative effort led by Renault, supported by a consortium of key industry players specialized in smart mobility, connectivity, and automation. The project includes Sigma, Seevia, Luce IT, Multiverse Computing, and Fivecomm, each contributing expertise in artificial intelligence, perception systems, vehicle automation, and advanced communications. Additionally, ASVIC benefits from the support of leading research institutions, including CTAG (Automotive Technology Center of Galicia) and iTEAM (Institute of Telecommunications and Multimedia Applications), ensuring the integration of the latest advancements in connectivity, cybersecurity, and intelligent transportation systems.
The project is funded by the Centro para el Desarrollo Tecnológico y la Innovación, E.P.E. and supported by the Ministerio de Ciencia e Innovación.
