TY - GEN
T1 - Reciprocal impact of autonomous vehicles and network resource management
AU - Sivrikaya, Fikret
AU - Khan, Manzoor Ahmed
AU - Bila, Cem
AU - Albayrak, Sahin
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported in part by the German Federal Ministry of Education and Research (BMBF) under the grant number 16KIS0580 and by the Federal Ministry of Transport and Digital Infrastructure (BMVi) under the grant number 16AVF1021A.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/30
Y1 - 2018/1/30
N2 - Autonomous driving is a vision that seems likely to be realized sooner than expected; the industry and research community are actively coordinating on achieving the goals of different levels of automation. One obvious and important aspect of autonomous driving is efficient and reliable connectivity both within and around the vehicle. Autonomous vehicles should be able to communicate with their environment and remote data analysis platforms in real-time, which qualifies the telecommunication industry as an important stakeholder in the autonomous driving ecosystem. In particular, the highly stringent connectivity requirements of an autonomous vehicle, its trajectory planning system, and the resource planning of the communication service provider are highly interdependent on each other. In this paper, we study the relationship between route planning systems in autonomous vehicles and resource management systems of telecom operators, explaining how a bidirectional interface among the two would induce higher efficiency on both ends. We also provide an overview of an urban test field for autonomous and connected driving in Berlin, which will serve as a testbed for experimenting with the concepts presented in this work.
AB - Autonomous driving is a vision that seems likely to be realized sooner than expected; the industry and research community are actively coordinating on achieving the goals of different levels of automation. One obvious and important aspect of autonomous driving is efficient and reliable connectivity both within and around the vehicle. Autonomous vehicles should be able to communicate with their environment and remote data analysis platforms in real-time, which qualifies the telecommunication industry as an important stakeholder in the autonomous driving ecosystem. In particular, the highly stringent connectivity requirements of an autonomous vehicle, its trajectory planning system, and the resource planning of the communication service provider are highly interdependent on each other. In this paper, we study the relationship between route planning systems in autonomous vehicles and resource management systems of telecom operators, explaining how a bidirectional interface among the two would induce higher efficiency on both ends. We also provide an overview of an urban test field for autonomous and connected driving in Berlin, which will serve as a testbed for experimenting with the concepts presented in this work.
KW - Autonomous driving
KW - local dynamic map
KW - network resource management
KW - proactive mobility management
KW - route planning
UR - http://www.scopus.com/inward/record.url?scp=85046256206&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046256206&partnerID=8YFLogxK
U2 - 10.1109/VNC.2017.8275640
DO - 10.1109/VNC.2017.8275640
M3 - Conference contribution
AN - SCOPUS:85046256206
T3 - IEEE Vehicular Networking Conference, VNC
SP - 231
EP - 234
BT - 2017 IEEE Vehicular Networking Conference, VNC 2017
A2 - Altintas, Onur
A2 - Casetti, Claudio
A2 - Meireles, Rui
A2 - Kirsch, Nicholas
A2 - Lo Cigno, Renato
PB - IEEE Computer Society
T2 - 2017 IEEE Vehicular Networking Conference, VNC 2017
Y2 - 27 November 2017 through 29 November 2017
ER -