Abstract

The automotive industry aims to deploy commercial level-5 fully autonomous self-driving vehicles (FA-SDVs) in a diverse range of benefit-driven concepts on city roads in the years to come. In all future visions of operating networks of FA-SDVs, humans are expected to intervene with some kind of remote supervisory role. Recent advances in cyber-physical systems (CPS) within the concept of Internet of Everything (IoE) using tactile internet (TI) teleport us to teleoperate remote objects within the cyber-world. Human-on-the-loop (HOTL) haptic teleoperation with an extension of human control and sensing capability by coupling with artificial sensors and actuators with an increased sense of real-time driving in the remote vehicle can help overcome the challenging tasks when the new driver - artificial intelligence (AI) agent - encounters an unorthodox situation that can't be addressed by the autonomous capabilities. This paper analyses HOTL real-time haptic delay-sensitive teleoperation with FA-SDVs, in the aspects of human-vehicle teamwork by establishing two similar remote parallel worlds --- real-world vehicle time-varying environment and cyber-world emulation of this environment, i.e., digital twins (DTs) --- in which a human telesupervisor (HTS), as a biological agent, can be immersed within a reasonable timescale with no cybersickness enabling omnipresence and a bidirectional flow of energy and information. The experiments conducted as a proof of concept of HOTL haptic teleoperation shows promising results and the potential of benefiting from the proposed framework.

Highlights

  • F ULLY autonomous systems are human-out-of-the-loop systems that single-handedly determine the right course of action when given an autonomous task

  • Humans may forget how to drive physically, but need to learn very well how to teleoperate FASDVs with location-independent remote control abilities using V2X technologies equipped with haptics and tactile internet (TI) to step in when the new driver — artificial intelligence (AI) — encounters an unexpected situation that can’t be handled by the autonomous capabilities

  • To close the literature gap in this field, in this paper, an in-depth discussion is provided in building an ecosystem that aims to establish a common ground for an ideal location-independent collaboration between skilled human telesupervisor (HTS) and intelligent fully autonomous self-driving vehicles (FA-SDVs)

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Summary

INTRODUCTION

F ULLY autonomous systems are human-out-of-the-loop systems that single-handedly determine the right course of action when given an autonomous task. Recent advances in cyberphysical systems (CPS) within the concepts of Internet of Everything (IoE) and Automation of Everything (AoE) [7] using tactile internet (TI) equipped with quality haptic feedback teleport us to teleoperate remote objects using digital twins (DTs), i.e., the virtual cyber-world embedded in the physical world In this context, many companies testing FA-SDVs are developing remote operation capabilities, where a human in a control centre can take over and safely manoeuvre FA-SDVs in case of malfunctions or emergencies [8]. In the rest of the paper, “human teleoperator” (i.e., master) and “invehicle teleoperator” (i.e., slave side) are titled as “human telesupervisor (HTS)” and “FA-SDV” respectively Despite their highly self-directed intelligent abilities, it would be unfair to expect SDVs to manage a highly unusual situation that even couldn’t be handled by a skilled human driver.

RELATED WORKS
Background of methodology
HOTL-HT-SDV framework
Result
MULTI-AGENT LEARNING WITHIN HOTL-HT-SDV
Multi-agent learning within HOTL-HT-SDV
Evaluation Team
Collaboration modes within HOTL-HT-SDV
FULL CONTROL
Proof of concept
DISCUSSION
CONCLUSIONS AND FUTURE DIRECTIONS
Full Text
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