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Directory

High-Level Overview

Glossary

Input

Data Framework

Performance Assurance

Scenario

Create

Format

Store

Environment

Query/Concretise

Allocate

Execute

Safety Argument

Coverage

Test/Evaluate

Safety Case

Decide

Audit

Use Cases

SAF Solutions

Submit Feedback

SUNRISE SAF Solutions

Store

Input Scenario Create Format Store Environment Query & Concretise Allocate Execute Safety Argument Coverage Test Evaluate Safety Case Decide Audit

ADScene

Provider: Renault SAS, Stellantis
Contact: eric.vaillant@renault.com
Description

ADScene is a scenario database and scenario description format that allows to create and manage digital traffic scenarios. Scenarios can be manually created or automatically extracted from driving data. ADScene allows to browse scenarios, to store them in containers with dedicated access rights and also provides scenario history (for versioning and traceability). ADScene can be queried to filter scenarios. ODD attributes are part of the possible filters.

Key Features
  • Scenario creation, storage and management
  • Scenario parameter statistics and distribution
  • Existing scenarios such as accident scenarios and real world driving scenarios
  • API for querying from external tools, like the SUNRISE Data Framework
How does this solution cover this SAF block?
  • Create block – ADScene allows both manual and automatic creation of scenarios coming from real world driving data.
  • Format block – ADScene furnishes a scenario data model for standardized scenario description.
  • Store block – ADScene provides tools to manage scenario storage, for example regarding access rights and versioning.
  • ADScene API allows for external querying, for example through the SUNRISE Data Framework.

AVL SCENIUS™

Provider: AVL List GmbH, Austria
Contact: heiko.scharke@avl.com
Description

The AVL SCENIUS™ is a comprehensive, end-to-end solution designed to meet the complex demands of ADAS/AD test management and safety validation. It supports the entire validation process — from managing requirements, defining and organizing tests to allocating them across diverse environments, coordinating execution, and enabling thorough result evaluation through a seamless, automated workflow.

Key Features
  • Automated Testing: Significantly reduce manual effort, allowing for more efficient testing processes and quicker turnaround times through a smart variety of reliable testing approaches.
  • Regulatory Compliance: Stay ahead of the curve with built-in compliance checks that ensure your system meets the latest safety standards and regulations.
  • Enhanced Traceability: Track requirements, tests, and results across the entire development lifecycle, ensuring nothing falls through the cracks.
  • Virtual Assessment: Leverage advanced features to conduct virtual assessments, proving safety and credibility in a controlled environment.
  • Real-time Analytics: Gain insights that help you make informed decisions and quickly identify and address issues.
  • Comprehensive Reporting: Generate detailed dashboards and reports on test results, helping you demonstrate system reliability and safety to stakeholders.
  • Seamless Integration: Painless integration with various CI/CD – CI/CT pipelines and interfaces, reducing complexity and ensuring smooth workflows.
How does this solution cover this SAF block?
  • Scenario Designer with full ASAM OpenX compatibility
  • Scenario Data Manager
  • Validation Project Manager
  • Test Definition Manager
  • Test Execution Manager
  • Test Analyzer
  • Reporting and Dashboarding
  • Safety Assessment
  • Requirement Manager
  • ODD Manager
  • Rich REST API to integrate in workflow and tools

IDIADA Scenario DB

Provider: Applus+ IDIADA, Spain
Contact: xavier.sellart@idiada.com, jesus.fuentes@idiada.com, patrick.fischer@idiada.com
Description

Applus+ IDIADA has developed a comprehensive scenario database providing standardized, validated test scenarios for advanced autonomous driving simulation and validation.

Key Features
  • Standardized Scenario Repository: Extensive collection of validated driving scenarios in ASAM OpenX standard format.
  • Comprehensive Coverage: Diverse scenarios encompassing urban, rural, proving ground and complex driving environments.
  • Simulation-Ready Datasets: Precisely structured and annotated scenarios for seamless integration with automotive simulation platforms.
  • Continuous Knowledge Integration: Regularly updated database leveraging IDIADA’s specialized autonomous driving engineering expertise.
How does this solution cover this SAF block?
  • Scenarios are provided in ASAM OpenX format, ensuring compatibility with the SUNRISE Data Framework.
  • Offers a structured and reliable repository ready for downstream simulation and testing.
  • Includes urban, rural, and proving ground scenarios to support a wide range of test needs.
  • Scenarios are annotated and formatted for direct integration with virtual testing platforms.

Safety Pool™ Scenario Database

Provider: University of Warwick
Contact: s.khastgir.1@warwick.ac.uk
Description

The Safety Pool™ Scenario Database is a secure, collaborative platform for storing, managing, and executing test scenarios for Connected and Autonomous Vehicle (CAV) technologies. It hosts a comprehensive library of scenarios that support the development and validation of Automated Driving Systems (ADS) through simulation, and real-world testing. The platform also enables users to create, format, and standardize scenarios for consistent use across different environments and tools.

Key Features
  • Supports scenario-based testing for the development and validation of Connected, Cooperative, and Automated Mobility (CCAM) systems in simulation.
  • Facilitates scenario creation, formatting, storage, and sharing in standardized formats (e.g., OpenSCENARIO).
  • Ensures reproducibility and traceability of testing through version control and scenario metadata.
  • Provides secure access control and data management for collaborative development and research.
How does this solution cover this SAF block?
  • Efficiently concretizes parameter spaces into optimized test scenarios to explore complex parameter interactions and critical conditions for automated testing.
  • Integrates testing objectives and orchestrates automated test execution, ensuring seamless data flow and traceability from scenario definition to execution.
  • Closes the loop with continuous data-driven optimization by analyzing test results in real time and dynamically refining future test cases to accelerate validation cycles and enhance scenario coverage, including boundary and failure exploration.

Safety Pool™ Studio

Provider: University of Warwick
Contact: s.khastgir.1@warwick.ac.uk
Description

Safety Pool™ Studio is a powerful web-based platform for authoring, editing, and validating traffic scenarios used in the testing of Automated Driving Systems (ADS). It offers an intuitive, no-code interface that enables users to rapidly generate scenarios in industry-standard formats such as OpenSCENARIO. Designed to support simulation-based development and validation, the Studio simplifies the process of creating complex, diverse, and high-quality scenarios for Connected and Autonomous Vehicle (CAV) testing.

Key Features
  • Enables users to create detailed driving scenarios through an intuitive visual interface without requiring programming expertise.
  • Exports scenarios in standardized formats such as OpenSCENARIO, ensuring interoperability with simulation platforms.
  • Allows users to design scenarios on real-world maps or test tracks with precision placement of vehicles, pedestrians, and infrastructure.
How does this solution cover this SAF block?
  • Efficiently concretizes parameter spaces into optimized test scenarios to explore complex parameter interactions and critical conditions for automated testing.
  • Integrates testing objectives and orchestrates automated test execution, ensuring seamless data flow and traceability from scenario definition to execution.
  • Closes the loop with continuous data-driven optimization by analyzing test results in real time and dynamically refining future test cases to accelerate validation cycles and enhance scenario coverage, including boundary and failure exploration.

Scenario Center

Provider: IKA – RWTH Aachen University, Germany
Contact: info@scenario.center
Description

Scenario.center is a scenario database that automatically builds a model of the Operational Design Domain (ODD) from traffic observations, makes the ODD systematically testable in simulation, and tracks the coverage.

Key Features
  • Automatically create a scenario-based model of the ODD based on traffic observations.
  • Analyse and compare traffic observations based on scenarios and their parameters.
  • Estimates the scenario and scenario parameter distributions based on the observed scenarios.
  • Search for specific traffic interactions and sequences of those.
  • Get scenarios as ASAM OpenSCENARIO and ASAM OpenDRIVE, ready for simulation in esmini and CARLA.
How does this solution cover this SAF block?
  • Create/Format/Store: Automatically analyses traffic observations and identifies situations that match scenarios. These identified scenarios are stored in a scenario database.
  • Query and Concretise: The scenario database allows to query observed scenarios and to sample from conditional distributions of scenarios and their parameters (conditioned by the query).
  • Coverage: With respect to the scenario concept of scenario.center, it can compute a coverage estimation.

StreetWise

Provider: TNO, The Netherlands
Contact: olaf.opdencamp@tno.nl, henk.goossens@tno.nl
Description

StreetWise is a methodology developed by TNO to use driving data to extract real-world scenarios, determine the statistics of these scenarios, and use the scenarios for assessing automated driving systems. To support the research and development of StreetWise, it comes with a concept database that contains real-world scenarios.

Key Features
  • Automatically mining scenarios from real-world driving data for creation of scenario database content.
  • Multivariate distributions of scenario parameter values are derived using statistical method.
  • Test scenario generation from stored scenario database information, via TNO GUI or API in OpenDRIVE and OpenSCENARIO format.
  • The estimated multivariate distributions can be used to determine the exposure of concrete scenarios and generate test scenarios that are not necessarily observed in real-world data.
How does this solution cover this SAF block?
  • TNO StreetWise provides a methodology to create a scenario database required for the scenario-based approach, covering the Scenario block as a whole, including the Create, Format and Store sub-blocks.
  • TNO StreetWise GUI and API facilitate the access between Environment – Query & Concretise and Scenario – Store.
  • TNO StreetWise enables the concretisation of test scenarios covering Environment – Query & Concretise.
  • Statistics derived from the created scenario database allow for coverage estimation on concrete scenario level.