5G NetMobil

5G NetMobil – 5G solutions for the connected mobility of the future

Co-funded by the Federal Ministry of Education and Research (BMBF)

5G-NetMobile project page

Duration: March 2017 – February 2020

The main aim of the 5G NetMobil project is to develop an all-encompassing communications infrastructure for tactile interconnected driving and demonstrate its advantages over autonomous driving in relation to road safety, environmental impact and traffic efficiency based solely on local sensor data.

While autonomous driving already promises more comfort and safety, tactile interconnected driving makes new driving strategies possible which further increase road traffic safety, significantly reduce CO² emissions and considerably improve traffic efficiency on the roads by better capacity management and reduced danger of traffic jams and accidents.

Implementing this vision into reality requires secure and robust communication for operating and control in real-time. Therefore, innovative 5G communications architecture with relevant information and communication technology will be developed in this research project which will enable the tactile internet for tactile interconnected driving. The integration of existing technologies such as Wireless 4G or IEEE 802.11p will also be considered in this context.

The main focus of the project at the Fraunhofer HHI is the development and investigation of innovative diversity, coexistence and network management approaches for the communication networks of the future to realise tactile interconnected driving.

Motivated by the high real-time and reliability demands, one main topic of the project covers diversity concepts such as multi-connectivity.

New network management concepts must be developed to realise this and support the high mobility demands of tactile interconnected driving.

The aim is to create efficient and scalable solutions which allow cognitive network management for tactile interconnected driving with the help of connections to all available data and the integration of predictive components.