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Automated vehicles are designed to operate safely under certain conditions – for example on specific types of roads, in certain weather conditions or traffic environments. But a key challenge remains: how can we systematically determine whether a vehicle’s capabilities actually match the environment in which it is expected to operate?

This is the focus of the new research project ODDmeTOD – Methods for defining, comparing and validating ODD and TOD for safe automated driving.

For automated driving, the Operational Design Domain (ODD) describes the conditions under which an automated driving system is designed to function. The project introduces the complementary concept of a Target Operational Domain (TOD) – a machine-readable description of the actual operating environment and its relevant conditions.

By systematically comparing the two, ODDmeTOD aims to identify gaps where the vehicle’s capabilities may not sufficiently cover the demands of the intended operating environment. These gaps can then be translated into safety-critical scenarios and minimum testing requirements. 

From broad testing to evidence that matters
A major potential benefit is more focused and traceable safety validation. Rather than simply increasing the amount of testing, the approach can help identify what really needs to be tested, why it matters and whether the relevant operating conditions have been sufficiently covered.

The project will combine simulation with selected physical testing to create a traceable evidence chain that can support safety assessment and, ultimately, approval of automated driving systems. The ambition is to contribute to safer deployment, more efficient validation and international standardisation. 

The project runs from June 2026 to January 2028 and is funded by Vinnova through FFI Traffic-safe automation. Partners are AstaZero, Einride, Applied Intuition, the University of Gothenburg and Mid Sweden University.