Taxonomy and Survey on Remote Human Input Systems for Driving Automation Systems

TL;DR

This paper surveys and proposes a taxonomy for remote human input systems in driving automation, aiming to standardize terminology and improve communication as automated driving scales up.

Contribution

It introduces a comprehensive taxonomy for remote human input approaches in driving automation, addressing the lack of a unified classification.

Findings

Identifies diverse approaches to remote human input in driving systems

Proposes a hierarchical taxonomy based on complexity levels

Highlights the need for standardized terminology in the field

Abstract

Corner cases for driving automation systems can often be detected by the system itself and subsequently resolved by remote humans. There exists a wide variety of technical approaches on how remote humans can resolve such issues. Over multiple domains, no common taxonomy on those approaches has developed yet, though. As the scaling of automated driving systems continues to increase, a uniform taxonomy is desirable to improve communication within the scientific community, but also beyond to policymakers and the general public. In this paper, we provide a survey on recent terminologies and propose a taxonomy for remote human input systems, classifying the different approaches based on their complexity.