Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing
The growing complexity of autonomous vehicle functionalities poses significant challenges for vehicle testing, validation, and regulatory approval. Despite the availability of various testing protocols and standards, a harmonized and widely accepted method specifically targeting the selection of cri...
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MDPI AG
2025-06-01
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| author | Balint Toth Zsolt Szalay |
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| collection | DOAJ |
| description | The growing complexity of autonomous vehicle functionalities poses significant challenges for vehicle testing, validation, and regulatory approval. Despite the availability of various testing protocols and standards, a harmonized and widely accepted method specifically targeting the selection of critical test scenarios—especially for safety assessments prior to public road testing—has not yet been developed. This study introduces a systematic methodology for selecting a minimum critical set of test scenarios tailored to an autonomous vehicle’s Operational Design Domain (ODD) and capabilities. Building on existing testing frameworks (e.g., EuroNCAP protocols, ISO standards, UNECE and EU regulations), the proposed method combines a structured questionnaire with a weighted cosine similarity based filtering mechanism to identify relevant scenarios from a robust database of over 1000 test cases. Further refinement using similarity metrics such as Euclidean and Manhattan distances ensures the elimination of redundant test scenarios. Application of the framework to real-world projects demonstrates significant alignment with expert-identified cases, while also identifying overlooked but relevant scenarios. By addressing the need for a structured and efficient scenario selection method, this work supports the advancement of systematic safety assurance for autonomous vehicles and provides a scalable solution for authorities and vehicle testing companies. |
| format | Article |
| id | doaj-art-fd4beb7792d2457e8b8c4071877d5a93 |
| institution | Matheson Library |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj-art-fd4beb7792d2457e8b8c4071877d5a932025-07-11T14:35:27ZengMDPI AGApplied Sciences2076-34172025-06-011513703110.3390/app15137031Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road TestingBalint Toth0Zsolt Szalay1Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem Rakpart 3, 1111 Budapest, HungaryDepartment of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem Rakpart 3, 1111 Budapest, HungaryThe growing complexity of autonomous vehicle functionalities poses significant challenges for vehicle testing, validation, and regulatory approval. Despite the availability of various testing protocols and standards, a harmonized and widely accepted method specifically targeting the selection of critical test scenarios—especially for safety assessments prior to public road testing—has not yet been developed. This study introduces a systematic methodology for selecting a minimum critical set of test scenarios tailored to an autonomous vehicle’s Operational Design Domain (ODD) and capabilities. Building on existing testing frameworks (e.g., EuroNCAP protocols, ISO standards, UNECE and EU regulations), the proposed method combines a structured questionnaire with a weighted cosine similarity based filtering mechanism to identify relevant scenarios from a robust database of over 1000 test cases. Further refinement using similarity metrics such as Euclidean and Manhattan distances ensures the elimination of redundant test scenarios. Application of the framework to real-world projects demonstrates significant alignment with expert-identified cases, while also identifying overlooked but relevant scenarios. By addressing the need for a structured and efficient scenario selection method, this work supports the advancement of systematic safety assurance for autonomous vehicles and provides a scalable solution for authorities and vehicle testing companies.https://www.mdpi.com/2076-3417/15/13/7031automated vehiclesautonomous drivingtest scenario catalogueproving ground testingvalidationhomologation |
| spellingShingle | Balint Toth Zsolt Szalay Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing Applied Sciences automated vehicles autonomous driving test scenario catalogue proving ground testing validation homologation |
| title | Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing |
| title_full | Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing |
| title_fullStr | Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing |
| title_full_unstemmed | Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing |
| title_short | Minimum Critical Test Scenario Set Selection for Autonomous Vehicles Prior to First Deployment and Public Road Testing |
| title_sort | minimum critical test scenario set selection for autonomous vehicles prior to first deployment and public road testing |
| topic | automated vehicles autonomous driving test scenario catalogue proving ground testing validation homologation |
| url | https://www.mdpi.com/2076-3417/15/13/7031 |
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