Framework for evaluating QoE for remote control of autonomous cars in mobile wireless networks

Abstract

This paper introduces framework for designing and evaluating the video adaptation controllers - i.e. the enablers for the growing market of user generated traffic. The main targets are the use-cases connected with emerging market of the autonomous cars or drones that require remote assistance of the operator upon on-board controller failure. To validate the proposed architecture authors have designed test cases that validate usability of the proposed solution for the uplink surveillance and monitoring traffic adaptation. We propose a systematic approach to combine real network traces, network modelling and emulation, video transcoder as a service and the use of no-reference QoE metrics in order to assure effective means for video controllers design and tuning. Authors have described architecture as well as results of comprehensive sensitivity tests of QoE in uplink for mobile WiMAX networks. The results show that the proposed framework provides valuable potential for development and evaluation answering the demand of emerging scenarios for mobile surveillance.