Performance assessment of ADAS in a representative subset of critical traffic situations
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910717503864832 |
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| author | Di Lillo, Luigi Triscari, Andrea Zhou, Xilin Dyro, Robert Li, Ruolin Pavone, Marco |
| author_facet | Di Lillo, Luigi Triscari, Andrea Zhou, Xilin Dyro, Robert Li, Ruolin Pavone, Marco |
| contents | As a variety of automated collision prevention systems gain presence within personal vehicles, rating and differentiating the automated safety performance of car models has become increasingly important for consumers, manufacturers, and insurers. In 2023, Swiss Re and partners initiated an eight-month long vehicle testing campaign conducted on a recognized UNECE type approval authority and Euro NCAP accredited proving ground in Germany. The campaign exposed twelve mass-produced vehicle models and one prototype vehicle fitted with collision prevention systems to a selection of safety-critical traffic scenarios representative of United States and European Union accident landscape. In this paper, we compare and evaluate the relative safety performance of these thirteen collision prevention systems (hardware and software stack) as demonstrated by this testing campaign. We first introduce a new scoring system which represents a test system's predicted impact on overall real-world collision frequency and reduction of collision impact energy, weighted based on the real-world relevance of the test scenario. Next, we introduce a novel metric that quantifies the realism of the protocol and confirm that our test protocol is a plausible representation of real-world driving. Finally, we find that the prototype system in its pre-release state outperforms the mass-produced (post-consumer-release) vehicles in the majority of the tested scenarios on the test track. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_16942 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Performance assessment of ADAS in a representative subset of critical traffic situations Di Lillo, Luigi Triscari, Andrea Zhou, Xilin Dyro, Robert Li, Ruolin Pavone, Marco Robotics As a variety of automated collision prevention systems gain presence within personal vehicles, rating and differentiating the automated safety performance of car models has become increasingly important for consumers, manufacturers, and insurers. In 2023, Swiss Re and partners initiated an eight-month long vehicle testing campaign conducted on a recognized UNECE type approval authority and Euro NCAP accredited proving ground in Germany. The campaign exposed twelve mass-produced vehicle models and one prototype vehicle fitted with collision prevention systems to a selection of safety-critical traffic scenarios representative of United States and European Union accident landscape. In this paper, we compare and evaluate the relative safety performance of these thirteen collision prevention systems (hardware and software stack) as demonstrated by this testing campaign. We first introduce a new scoring system which represents a test system's predicted impact on overall real-world collision frequency and reduction of collision impact energy, weighted based on the real-world relevance of the test scenario. Next, we introduce a novel metric that quantifies the realism of the protocol and confirm that our test protocol is a plausible representation of real-world driving. Finally, we find that the prototype system in its pre-release state outperforms the mass-produced (post-consumer-release) vehicles in the majority of the tested scenarios on the test track. |
| title | Performance assessment of ADAS in a representative subset of critical traffic situations |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.16942 |