With the emergence of highly automated and autonomous driving vehicles, rigorous requirements in terms of responsiveness, security, resiliency and scalability are needed to enable new services that improve efficiency and safety on the road. The recent progress on 5G ultra reliable and low latency communications is paving the way to novel solutions that address these challenging requirements. To this end, a plethora of paradigms, (such as Fog/Multi-Access Edge computing, Software Defined Networking, Network Function Virtualization); emerging protocols for V2X communication (LTE-V, C-V2X, etc.) and advanced localization/navigation systems (3D High Definition maps, Advanced Driver Assistance Systems) have been proposed or are still under development to support future autonomous vehicles.
In addition, given the ever-increasing complexity of future networks, adding intelligence and agility to the control plane through Artificial Intelligence (AI) and Machine Learning (ML) becomes a promising trend to improve road monitoring and network resource allocation. Therefore, in the path towards fully autonomous and safe coordinated driving, it is crucial to investigate how and up to which point the most recent computing and communication paradigms are able to meet the requirements of autonomous driving, be self-learning and adaptive to radio conditions and to the heterogeneity of new applications in terms of data rates, latency and hyper-connectivity.
In the spirit of WCNC, this workshop aims at favoring a multidisciplinary, cross-layer perspective to computing and communication technologies for autonomous and cooperative driving, bringing together researchers, developers, and practitioners from academia and industry.
We invite paper submissions including, but not limited to the topics listed below:
Use case requirements for autonomous vehicles
Cellular vehicle-to-everything (C-V2X) communication
Multi-Access Edge computing for Ultra-reliable and low-latency communication
AI-Empowered Vehicular Networks
SDN-enabled Vehicular networks
Network slicing and multi-tenancy in next generation of vehicular networks
HD dynamic mapping and accurate positioning (GNSS)
Simultaneous Localization and Mapping (SLAM)
ADAS systems for autonomous vehicles
|Fog/Edge computing for vehicular networks
Fog/Edge-based zero-time handover mechanisms
Mobility-aware spectrum sharing
Caching techniques for enabling ultra-low latency services.
Named Data Networking (NDN) for autonomous vehicles
Big Data Prescriptive analytics for resource allocation, network slicing, cache placement, etc.