Core Topics


Automated and networked driving –
the DIGINET-PS perspective

 

DigiNet-PS goes beyond the traditional practice of building intelligence into the vehicle alone. By distributing the computational load across vehicles, transport infrastructure (roadside units, RSU) and digitized street objects such as the cloud, it follows a decentralized model. In other words, three distinct domains – vehicle, street infrastructure and cloud – which compute their decisions autonomously, are networked to allow exchanges of information to flow between them.


Intelligent Vehicle

Intelligence by sharing tasks and outsourcing uncritical functions

Cloud

Collecting and computing data in the backend to support the overall system

Intelligent Infrastructure

Road Side Units connecting sensors talking to vehicles and offering local services.

Machine Learning

AI via implementing Machine Learning Approaches in combination with ADA

Edge Computing

Enabling low Latency and location aware services.

Advanced Data Analytics

ADA enables Predictive analytics to support operation of  complex systems

Software Defined Networking

SDN allows the necessary flexibility to connect all parts of the platform

Vehicle-to-X communication

Distributed operation requires flexible communication for lowest latency and minimized data quantity

Flexible Transport & Backhaul Network

Backhaul Network fostering latency demands in distributed systems

Street Digitization

Supports a holistic system approach by deploying: parking, traffic, weather, environmental, road condition and many more sensors

Application Development

Multi-Level service development to address all active and passive stakeholders

Evolution of the Ecosystem

The DigiNet-PS platform will be the foundation to develop future services