| Autor: |
Medaglini, A., Bartolini, S., Di Massa, V., Dini, F. |
| Předmět: |
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| Zdroj: |
Ada User Journal; Sep2022, Vol. 43 Issue 3, p177-186, 10p |
| Abstrakt: |
Nowadays, the innovations of AI and other automated decision-making software are spreading to many different areas. The automotive field in particular is rapidly shifting towards the concepts of Advanced Driver Assistance Systems (ADAS), which could bring huge benefits in the future. However, before being able to use these tools, many assurances are required regarding their functioning and safety. To this end, several control techniques exist to evaluate the performance of this software, but a reliable and repeatable method for evaluating complex scenarios and corner cases is still lacking. In this paper, we propose a suite of tools for the generation and analysis of synthetic tests, aimed at evaluating and analyzing the functioning of autonomous driving systems in order to measure their effectiveness and drive their development. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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