Review of Simulation Frameworks and Standards Related to Driving Scenarios

Schnelle, Scott C.; Salaani, M. Kamel; Rao, Sughosh J.; Barickman, Frank S.; Elsasser, Devin · 2019 · ROSA P / United States. Department of Transportation. National Highway Traffic Safety Administration

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Summary

This 2019 report by the National Highway Traffic Safety Administration (NHTSA) addresses the lack of standardized frameworks for simulating driving scenarios, a critical gap in the development and validation of SAE Level 4 and 5 Automated Driving Systems (ADS). The research is motivated by the industry reliance on computer simulation to test edge cases and system performance efficiently, as physical testing alone cannot probabilistically cover all high-risk scenarios. The authors aim to identify existing standards that could serve as an open interface for reading and writing scenario data, thereby enabling a shareable database of scenarios to accelerate ADS development and safety assessment. The study employs a comprehensive literature review and market summary to evaluate existing simulation frameworks, standards, and software. The scope focuses specifically on methods for describing "road and static content" and "dynamic content," treating the ADS as a black box to standardize inputs and outputs. The review categorizes findings into simulation standardization projects (e.g., RAND, PEGASUS), scenario specification formats (e.g., OpenX, RoadXML, GeoJSON), co-simulation architectures (e.g., IEEE 1516, ASAM XIL), and vehicle dynamics fidelity standards. Additionally, the report provides an overview of ADS subsystems—sensing, perception, planning, and control—and various simulation methodologies, including model-in-the-loop, hardware-in-the-loop, and vehicle-in-the-loop approaches. The findings indicate that no single existing framework has been widely adopted across all ADS stakeholders or simulation platforms. However, the OpenX suite (comprising OpenCRG, OpenDRIVE, and OpenSCENARIO) and RoadXML emerged as the most widely supported standards for defining roadways, networks, and scenarios. These standards utilize Extensible Markup Language (XML) to encode structured data, facilitating sharing and publication. Despite their broad compatibility, the report notes that these standards are still under development and lack certain elements necessary for fully assessing ADS performance in simulated environments. Furthermore, while probabilistic sensor models offer a reasonable trade-off between computational efficiency and realism, high-fidelity physics-based models remain computationally intensive. The significance of this work lies in its identification of the current state of simulation standardization, highlighting that while interoperable formats like OpenX exist, they are not yet sufficient for comprehensive ADS validation. The report concludes that future efforts must focus on experimenting with these frameworks to assess their compatibility and further developing standards to include missing scenario elements. Establishing a common, open-format framework for scenario data is essential for creating a reusable knowledge base of safety-relevant scenarios, which will support the rigorous verification and validation required for the safe deployment of highly automated vehicles.

Key finding

No existing simulation framework has been widely adopted among ADS stakeholders, though OpenX and RoadXML standards appear to be the most widely supported by available simulation applications.

Methodology

review

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• situational awareness
• simulator validity fidelity

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Applied Guidance: standards test procedures
• Methodological Resource: tool software, validation psychometrics