A new Taxonomy for Automated Driving: Structuring Applications based on their Operational Design Domain, Level of Automation and Automation Readiness

TL;DR

This paper proposes an integrated taxonomy linking operational design domains, SAE automation levels, and technology maturity to better compare and analyze automated driving systems.

Contribution

It introduces a new taxonomy and maturity model that enhance the structuring and comparison of automated vehicle systems across different operational and technological parameters.

Findings

The taxonomy improves differentiation of automated vehicle systems.

The maturity model facilitates systematic comparison and identification of research gaps.

Application to existing vehicles demonstrates its practical utility.

Abstract

The aim of this paper is to investigate the relationship between operational design domains (ODD), automated driving SAE Levels, and Technology Readiness Level (TRL). The first highly automated vehicles, like robotaxis, are in commercial use, and the first vehicles with highway pilot systems have been delivered to private customers. It has emerged as a crucial issue that these automated driving systems differ significantly in their ODD and in their technical maturity. Consequently, any approach to compare these systems is difficult and requires a deep dive into defined ODDs, specifications, and technologies used. Therefore, this paper challenges current state-of-the-art taxonomies and develops a new and integrated taxonomy that can structure automated vehicle systems more efficiently. We use the well-known SAE Levels 0-5 as the "level of responsibility", and link and describe the ODD at an intermediate level of abstraction. Finally, a new maturity model is explicitly proposed to improve the comparability of automated vehicles and driving functions. This method is then used to analyze today's existing automated vehicle applications, which are structured into the new taxonomy and rated by the new maturity levels. Our results indicate that this new taxonomy and maturity level model will help to differentiate automated vehicle systems in discussions more clearly and to discover white fields more systematically and upfront, e.g. for research but also for regulatory purposes.