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Supplemental Taxonomy for SAE L3-L4: A Tri-Layer Environmental Grading Framework

  • Chengxi Hu
  • , Sikai Chen
  • , Samuel Labi
  • , Hongliang Ding
  • , Hyungchul Chung
  • , Tiantian Chen*
  • *Corresponding author for this work
  • Korea Advanced Institute of Science and Technology
  • University of Wisconsin
  • Purdue University
  • Southwest Jiaotong University

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

The SAE taxonomy classifies autonomous driving levels based on how driving responsibilities are allocated between human and automated systems. However, it fails to specify critical environmental influences, which result in safety concerns, ambiguous performance expectations, and barriers to commercialization. The purpose of this paper is to fill this gap by introducing a Tri-layer Environmental Grading Framework (TEGF), which is a structured system that evaluates autonomous vehicle adaptability across built, natural, and traffic environments. The TEGF maps environmental favorability against the perception capabilities that are required for safe autonomous operation by quantifying environmental favorability through expert assessments. Our framework focuses specifically on SAE Levels 3 and 4, which we categorize into five tiers of adaptability (A-E). The supplementary classification clarifies operational boundaries and system expectations, thereby guiding technological development, regulatory frameworks, and public understanding of autonomous driving. By incorporating critical environmental dimensions into the SAE taxonomy, TEGF enhances the precision of the SAE taxonomy and provides a solid foundation for developing, testing, and deploying safe and reliable autonomous vehicles.

Original languageEnglish
Title of host publicationIEEE Intelligent Transportation Systems Conference, ITSC 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2727-2733
Number of pages7
ISBN (Electronic)9798331524180
DOIs
Publication statusPublished - Nov 2025
Event28th International Conference on Intelligent Transportation Systems, ITSC 2025 - Gold Coast, Australia
Duration: 18 Nov 202521 Nov 2025

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN (Print)2153-0009
ISSN (Electronic)2153-0017

Conference

Conference28th International Conference on Intelligent Transportation Systems, ITSC 2025
Country/TerritoryAustralia
CityGold Coast
Period18/11/2521/11/25

Keywords

  • automation level
  • autonomous vehicles
  • environmental elements
  • operational design domain
  • taxonomy

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