Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases
Existing testing methods for Automatic Emergency Braking (AEB) systems mostly rely on standard-based qualitative analysis of specific scenarios, with a focus on whether collisions occur. To explore scenarios beyond the standard conduct, a comprehensive testing model construction and analysis, and pr...
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| Format: | Article |
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MDPI AG
2023-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/1/173 |
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| author | Renhao Rao Changcai Cui Liang Chen Tianfang Gao Yuan Shi |
| author_facet | Renhao Rao Changcai Cui Liang Chen Tianfang Gao Yuan Shi |
| author_sort | Renhao Rao |
| collection | DOAJ |
| description | Existing testing methods for Automatic Emergency Braking (AEB) systems mostly rely on standard-based qualitative analysis of specific scenarios, with a focus on whether collisions occur. To explore scenarios beyond the standard conduct, a comprehensive testing model construction and analysis, and provide a more quantitative evaluation of AEB performance, this study extracted three typical hazardous driving scenarios from the KITTI (The Automated Driving dataset was created by the Karlsruhe Institute of Technology in Germany and the Toyota Institute of Technology in the United States) naturalistic driving dataset using kinematic data. A DME (Data Missing Estimation) scene construction method was proposed, and these scenarios were simulated and reconstructed in PRESCAN (PRESCAN is an automotive simulation software owned by Siemens, Munich, Germany). A C-AEB (Curve-Automatic Emergency Braking) testing model was developed and tested based on simulations. Finally, a BCEM (Boundary collision evaluation model) was proposed to quantitatively evaluate AEB performance. The focus of the analysis was on the identified cornering scenario A (severely failed AEB scenario). A C-AEB testing model was constructed based on the DME scene construction method for this cornering AEB failure scenario, and it was evaluated using the BCEM. The study found that the average performance degradation rate (performance degradation rate refers to the ratio of AEB performance in the current scenario compared to the standard straightaway test) of the AEB system in this cornering scenario reached 75.44%, with a maximum performance degradation rate of 89.47%. It was also discovered that the severe failure of AEB in this cornering scenario was mainly caused by sensor system perception defects and limitations of traditional AEB algorithms. This fully demonstrates the effectiveness of our testing and evaluation methodology. |
| first_indexed | 2024-03-08T15:12:43Z |
| format | Article |
| id | doaj.art-c5392ec7a1b7478d82895235ab2a656c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-08T15:12:43Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-c5392ec7a1b7478d82895235ab2a656c2024-01-10T14:51:12ZengMDPI AGApplied Sciences2076-34172023-12-0114117310.3390/app14010173Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner CasesRenhao Rao0Changcai Cui1Liang Chen2Tianfang Gao3Yuan Shi4Institute of Manufacturing Engineering, Huaqiao University, Xiamen 361021, ChinaInstitute of Manufacturing Engineering, Huaqiao University, Xiamen 361021, ChinaMotor Vehicle Quality Supervision and Inspection Center, Xiamen Institute of Product Quality Supervision and Inspection, Xiamen 361004, ChinaMotor Vehicle Quality Supervision and Inspection Center, Xiamen Institute of Product Quality Supervision and Inspection, Xiamen 361004, ChinaMotor Vehicle Quality Supervision and Inspection Center, Xiamen Institute of Product Quality Supervision and Inspection, Xiamen 361004, ChinaExisting testing methods for Automatic Emergency Braking (AEB) systems mostly rely on standard-based qualitative analysis of specific scenarios, with a focus on whether collisions occur. To explore scenarios beyond the standard conduct, a comprehensive testing model construction and analysis, and provide a more quantitative evaluation of AEB performance, this study extracted three typical hazardous driving scenarios from the KITTI (The Automated Driving dataset was created by the Karlsruhe Institute of Technology in Germany and the Toyota Institute of Technology in the United States) naturalistic driving dataset using kinematic data. A DME (Data Missing Estimation) scene construction method was proposed, and these scenarios were simulated and reconstructed in PRESCAN (PRESCAN is an automotive simulation software owned by Siemens, Munich, Germany). A C-AEB (Curve-Automatic Emergency Braking) testing model was developed and tested based on simulations. Finally, a BCEM (Boundary collision evaluation model) was proposed to quantitatively evaluate AEB performance. The focus of the analysis was on the identified cornering scenario A (severely failed AEB scenario). A C-AEB testing model was constructed based on the DME scene construction method for this cornering AEB failure scenario, and it was evaluated using the BCEM. The study found that the average performance degradation rate (performance degradation rate refers to the ratio of AEB performance in the current scenario compared to the standard straightaway test) of the AEB system in this cornering scenario reached 75.44%, with a maximum performance degradation rate of 89.47%. It was also discovered that the severe failure of AEB in this cornering scenario was mainly caused by sensor system perception defects and limitations of traditional AEB algorithms. This fully demonstrates the effectiveness of our testing and evaluation methodology.https://www.mdpi.com/2076-3417/14/1/173intelligent networked vehiclessafetydangerous scene extractionrebuildsimulation test |
| spellingShingle | Renhao Rao Changcai Cui Liang Chen Tianfang Gao Yuan Shi Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases Applied Sciences intelligent networked vehicles safety dangerous scene extraction rebuild simulation test |
| title | Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases |
| title_full | Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases |
| title_fullStr | Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases |
| title_full_unstemmed | Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases |
| title_short | Quantitative Testing and Analysis of Non-Standard AEB Scenarios Extracted from Corner Cases |
| title_sort | quantitative testing and analysis of non standard aeb scenarios extracted from corner cases |
| topic | intelligent networked vehicles safety dangerous scene extraction rebuild simulation test |
| url | https://www.mdpi.com/2076-3417/14/1/173 |
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