Toward an Agricultural Operational Design Domain: A Framework

TL;DR

This paper introduces the Ag-ODD Framework, a structured approach to define, verify, and standardize the operational environment of autonomous agricultural systems, addressing unique challenges in complex agricultural settings.

Contribution

The paper presents the first comprehensive framework specifically designed for agricultural operational design domains, integrating environmental description, a 7-layer model extension, and an iterative verification process.

Findings

The Ag-ODD Framework enables unambiguous environmental descriptions.

It supports verification of operational boundaries against logical scenarios.

Demonstrative use cases show improved standardization and scalability.

Abstract

The agricultural sector increasingly relies on autonomous systems that operate in complex and variable environments. Unlike on-road applications, agricultural automation integrates driving and working processes, each of which imposes distinct operational constraints. Handling this complexity and ensuring consistency throughout the development and validation processes requires a structured, transparent, and verified description of the environment. However, existing Operational Design Domain (ODD) concepts do not yet address the unique challenges of agricultural applications. Therefore, this work introduces the Agricultural ODD (Ag-ODD) Framework, which can be used to describe and verify the operational boundaries of autonomous agricultural systems. The Ag-ODD Framework consists of three core elements. First, the Ag-ODD description concept, which provides a structured method for unambiguously defining environmental and operational parameters using concepts from ASAM Open ODD and CityGML. Second, the 7-Layer Model derived from the PEGASUS 6-Layer Model, has been extended to include a process layer to capture dynamic agricultural operations. Third, the iterative verification process verifies the Ag-ODD against its corresponding logical scenarios, derived from the 7-Layer Model, to ensure the Ag-ODD's completeness and consistency. Together, these elements provide a consistent approach for creating unambiguous and verifiable Ag-ODD. Demonstrative use cases show how the Ag-ODD Framework can support the standardization and scalability of environmental descriptions for autonomous agricultural systems.