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An end-to-end 5G automotive ecosystem for autonomous driving vehicles

: Raddo, T.R.; Cimoli, B.; Sirbu, B.; Rommel, S.; Tekin, T.; Tafur Monroy, I.


Dingel, B.B. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Broadband Access Communication Technologies XIV : 4-5 February 2020, San Francisco, California
Bellingham, WA: SPIE, 2020 (Proceedings of SPIE 11307)
ISBN: 978-1-5106-3377-3
ISBN: 978-1-5106-3378-0
Paper 1130705, 10 pp.
Conference "Broadband Access Communication Technologies" <14, 2020, San Francisco/Calif.>
Conference Paper
Fraunhofer IZM ()

The fifth-generation (5G) of mobile systems is considered a key enabler technology for autonomous driving vehicles. This is due to its ultra-low latency, high-capacity, and network reliability. In this paper, a full end-to-end 5G automotive platform for benchmarking, certificating, and validating distinct use cases in cooperative intelligent transport systems, is proposed. Such an automotive platform enables fast service creation with open-access and on demand services designed for public use as well as for innovative use cases validation such as highway chauffeur system, truck platooning, and real-time perceptive intersection, to name a few. The distinct set of technologies that compose the end-to-end 5G automotive ecosystem framework is described. The holistic 5G automotive ecosystem can handle system and networking interoperability, handover between mobile cells, mobile edge computing capabilities including network slicing, service orchestration, and security. Moreov er, the latency performance of a vehicular network with two vehicles is experimentally addressed by using the holistic platform. Up- and down-stream packet transmissions between the two vehicles in an open environment with real-traffic conditions is considered. The results pave the way towards latency levels within the range of 5G key performance indicators and consequently enabling autonomous driving systems. The 5G platform can be further useful for governmental agencies to define new policies and regulations, being able to address critical points such as data protection, liability, and legal obligation, regardless whether systems are partially or fully automated.