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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

Decide

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

6S: Scenarios Database, Statistic Structured Space for Smart Sampling

Provider: VEDECOM, France
Contact: laurent.durville@vedecom.fr
Description

VEDECOM has developed and validated across multiple use cases a scenario sampling tool for ADAS testing, designed to reduce the testing budget while providing statistically rigorous performance guarantees. The tool enables the inference of the true accident rate of the ADAS from a limited number of test scenarios, ensuring a controlled uncertainty level and relying on real-world driving data observations.

Key Features
  • Structured critical scenario selection ensuring full behavioral coverage with controlled sample size.
  • Reduces test volume, accelerates execution, and quantifies residual risk based on test outcomes.
  • Statistical guarantee through absence of accidents on the critical sample, with improved precision over random sampling.
  • Guides validation planning for ADAS.
How does this solution cover this SAF block?
  • Efficiently covers the full behavioral space by selecting one critical scenario per zone, ensuring complete and representative coverage with minimal test effort.
  • Provides statistical guarantees of safety through accident-free validation on critical samples, with precise quantification of residual risk.
  • Accelerates validation by optimizing sample size, integrating concrete scenario data and statistically inferenced ones.
  • Offers a rigorous operational framework for planning, executing, and justifying ADAS and autonomous system validation campaigns.

ADAS/ADS FOT Tool

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

ADAS/ADS FOT Tool is a testing and data management platform developed by Applus+ IDIADA for evaluating the performance, safety, and impact of autonomous functions under actual operating conditions.

Key Features
  • Enables open-road based testing for validating ADAS and Autonomous Driving Systems (ADS) in real-world scenarios, across all ODD conditions.
  • Processes real-world driving data to identify and classify encountered scenarios, assessing how the intended ODD and scenario diversity is covered.
  • Data acquisition is based on event detection, vehicle state, and test objectives, ensuring efficient use of resources while capturing relevant insights.
  • Structures large-scale data into a validation framework that supports KPI reporting, behavioral analysis, and regression tracking.
How does this solution cover this SAF block?
  • Demonstrates system safety and robustness in dynamic, unpredictable environments, supporting real-world validation of intended functionality.
  • Captures rare and unanticipated behaviors or interactions that may not be covered in synthetic or controlled testing, enhancing scenario completeness.
  • Validates that the system behaves consistently and within safe boundaries across the complete ODD.
  • Generates structured, real-world performance data linked to specific ODD segments, enabling traceability and supporting the safety case with empirical evidence.

AVL CAMEO

Provider: AVL List GmbH, Austria
Contact: marijn.hollander@avl.com
Description

AVL CAMEO is a validation and verification software that supports test sequencing, AI-driven active Design of Experiments (DoE), and optimization. It provides a comprehensive frontloading solution that significantly enhances testing efficiency, reducing time, effort, and resource consumption. In ADAS testing, CAMEO enables systematic, scenario-based validation and optimization of systems through real-time test automation and intelligent data analysis.

Key Features
  • Facilitates scenario-based testing for CCAM system development through automated execution of test scenarios across simulation environments, hardware-in-the-Loop (HiL) systems, and proving grounds.
  • Leverages Active Design of Experiments (ADoE) and Machine Learning (ML) techniques to identify and prioritize critical scenario parameters for efficient validation.
  • Guarantees reproducibility of test results, supporting regulatory compliance and consistent system performance evaluation.
How does this solution cover this SAF block?
  • Automatically retrieves and executes relevant test scenarios across simulation, HiL, and real-world environments, based on predefined ODD, behavioral, and test objective inputs.
  • Integration of ADoE enables intelligent sampling and concretization of logical scenarios, efficiently deriving concrete scenarios that target high-risk or under-tested areas.
  • Ensures traceability and reproducibility of concrete test scenarios and their outcomes, supporting iterative scenario refinement and regulatory compliance.
  • Enables closed-loop testing by using test feedback to guide future scenario selection and concretization for targeted safety validation.

AVL Integration Core™ HIL/VIL

Provider: AVL List GmbH, Austria
Contact: niklas.braun@avl.com
Description

Powerful integration and simulation HW/SW platform to enable real-time testing of ADAS/AD ECUs in a HIL or VIL environment, together with multiple sensor simulations.

Key Features
  • Powerful real-time HW platform with support for multiple GPUs to simulate various sensors in parallel on a HIL or VIL.
  • Integration Core can be combined with 3rd-party components to enable rest-bus simulation, failure injection, cybersecurity testing, etc.
  • Supports multiple environment simulation providers.
  • Component manager to configure and operate sensor stimulators and/or sensor injection units in real time.
  • AVL SCENIUS™ can be operated in parallel on the Integration Core to plan, manage, and execute test cases on the HIL or VIL.
How does this solution cover this SAF block?
  • Enables real-time execution of test scenarios in physical or hybrid environments, validating ADAS/AD ECUs with high-fidelity sensor and environment simulation.
  • Supports multiple GPUs for parallel sensor simulation, integrates with third-party tools for rest-bus, failure, and cybersecurity testing.
  • Ensures configurability and real-time operation via its Component Manager.
  • Flexible across diverse ODDs and test setups, enabling harmonized and scalable validation workflows.

AVL Scenario Simulator™

Provider: AVL List GmbH, Austria
Contact: simon.terres@avl.com
Description

Integration and simulation platform to co-simulate models and software artifacts for virtual testing with parallel execution.

Key Features
  • Parallel simulations on local machine or scaled in cloud enable large scale parameter variations and high-frequency CI/CD pipelines for continuous testing.
  • Included performant CPU-only object-based sensor models and vehicle dynamics.
  • Open interfaces for integration of custom models or tools.
  • Standardized sensor interface and result visualization via ASAM OSI® (Open Simulation Interface).
How does this solution cover this SAF block?
  • Scenario engine with support of ASAM OpenSCENARIO® XML standard.
  • Customizable interfaces to integrate various simulation models and tools for complex virtual prototypes.
  • Open API facilitates toolchain integration with Allocation modules for test automation.
  • Open result formats (CSV, ASAM OSI®) enable compatibility with downstream safety argumentation.

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 PG Testing

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

Applus+ IDIADA provides proving ground testing as a critical intermediate step between simulation and public road testing, enabling controlled, repeatable, and safe evaluation of CCAM systems. Within a closed and instrumented environment, complex scenarios under realistic physical conditions can be validated, while eliminating uncontrolled variables.

Key Features
  • Enables safe testing using soft pedestrian dummies, vehicles, and cyclists that minimize damage upon contact.
  • Supports coordinated movement of multiple robotic actors and the vehicle under test to replicate high-risk scenarios.
  • Configurable road geometries and signage allow testing under varied and complex ODD conditions.
  • High-resolution tracking systems and synchronized video enable detailed post-test analysis and sensor validation.
How does this solution cover this SAF block?
  • Allows safe exploration of edge cases that are dangerous for open-road testing, ensuring behavioral safety thresholds are met.
  • Confirms that system behavior observed in simulation translates accurately to real-world dynamics and sensor conditions.
  • Provides documented results under defined conditions, contributing to the overall safety case and traceability of development decisions.

IDIADA XiL Services

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

Applus+ IDIADA offers advanced XiL services, from Software-in-the-Loop to Vehicle-in-the-Loop testing for ADAS and Autonomous vehicles validation and engineering development.

Key Features
  • Advanced Automotive Testing: IDIADA’s XiL solutions leverage cutting-edge facilities (including static & dynamic driving simulators, hardware-in-the-Loop racks, etc.) for comprehensive vehicle system validation.
  • Global Automotive Certification: Provides internationally recognized testing and homologation services integrated with XiL technologies.
  • End-to-End Engineering Support: Offers complete engineering solutions from simulation and development to prototype testing and certification.
How does this solution cover this SAF block?
  • Multi-Environment Test Execution (including Automation & Traceability) to run allocated test cases in any environment.
  • The execution results help to measure scenario and requirement coverage and provide data for pass/fail analysis and gap identification.

Neural Surrogate Models

Provider: University of Trento, Italy
Contact: mauro.dalio@unitn.it
Description

Service to construct neural surrogate models of system performance across a logical scenario with quantified confidence.

Key Features
  • Synthetic models of systems tracking system evolution
  • Ex-post quantification of KPIs for different risks in different regions of the logical scenario
  • Identification of failure modes
  • Fast, low computational burden permits the derivation of prudent speed recommendations against unexpected events during system operation
How does this solution cover this SAF block?
  • It serves as a surrogate model for “Execute” and “Test Evaluate,” providing predictions with quantified confidence.
  • Create efficient summary models that synthesize a system’s performance across a logical scenario with bounded confidence.
  • Analyze the system ex-post, quantifying risks and failure modes for different types of events.
  • Derive prudent speed functions to prevent those risks.
  • Query on new concrete scenarios not initially used, returning answers with quantified confidence/uncertainty, reducing the need for repeated testing.

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.