Research Article
Software-Defined Approach for Communication in Autonomous Transportation Systems
@ARTICLE{10.4108/eai.14-7-2017.152924, author={Piyush Dhawankar and Mohsin Raza and Hoa Le-Minh and Nauman Aslam}, title={Software-Defined Approach for Communication in Autonomous Transportation Systems}, journal={EAI Endorsed Transactions on Energy Web}, volume={4}, number={12}, publisher={EAI}, journal_a={EW}, year={2017}, month={7}, keywords={Autonomous driving Vehicles (ADVs); Software Defined Network (SDN); Network Function Virtualization (NFV); Vehicle-to-Vehicle (V2V); Vehicle--to-Infrastructure (V2I); Vehicle-to-Everything (V2X); Road-Side-Units (RSUs); On-Board-Units (OBUs); Evolved Packet Core (EPC).}, doi={10.4108/eai.14-7-2017.152924} }
- Piyush Dhawankar
Mohsin Raza
Hoa Le-Minh
Nauman Aslam
Year: 2017
Software-Defined Approach for Communication in Autonomous Transportation Systems
EW
EAI
DOI: 10.4108/eai.14-7-2017.152924
Abstract
Autonomous driving technology offers a promising solution to reduce road accidents, traffic congestion, and fuel consumption. The management of vehicular networks is challenging as it demands mobility, location awareness, high reliability and low latency of data traffic. In this paper, we propose a novel communication architecture for vehicular network with 5G Mobile Networks and SDN technologies to support multiple core networks for autonomous vehicles and to tackle the potential challenges raised by the autonomous driving vehicles. Data requirements are evaluated for vehicular networks with respect to number of lanes and cluster size, to efficiently use the frequency and bandwidth. Also, the network latency requirements are analysed, which are mandatory constraints for all the applications where real time end-to-end communication is necessary. A test environment is also formulated to evaluate improvement in vehicular network using SDN-based approach over traditional core networks.
Copyright © 2017 Piyush Dhawankar et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.