Abstract
Ensuring autonomous driving systems’ safety, reliability, and trustworthiness is paramount to preventing incorrect or unexpected system behaviors and hazardous scenarios. However, due to the complexity of such systems and the immense search space of possible scenarios, testing could be infeasible, necessitating the need to detect critical situations during operation. This paper proposes a hybrid approach that combines qualitative reasoning and object detection to prevent and discover critical driving scenarios. The proposed approach relies on identifying spatiotemporal patterns of detected objects in the driving environment that are indicative of critical scenarios, such as specific changes in movement or physical impossibilities. We evaluate the approach’s effectiveness on real-world driving data and demonstrate its ability to identify critical driving situations successfully. Moreover, we discuss the challenges associated with the approach and outline future research activities.
Originalsprache | englisch |
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Titel | Artificial Intelligence. ECAI 2023 International Workshops |
Untertitel | XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 – October 4, 2023, Proceedings, Part I |
Erscheinungsort | Cham |
Herausgeber (Verlag) | Springer |
Seiten | 156-172 |
ISBN (elektronisch) | 978-3-031-50396-2 |
ISBN (Print) | 978-3-031-50395-5 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2023 |
Veranstaltung | Trustworthy AI for Safe & Secure Traffic Control in Connected & Autonomous Vehicles: TACTIFUL 2023 - Kraków, Polen Dauer: 1 Okt. 2023 → 1 Okt. 2023 https://ceai.agh.edu.pl/45-eai-tactful23-workshop |
Publikationsreihe
Name | Communications in Computer and Information Science |
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Band | 1947 |
Workshop
Workshop | Trustworthy AI for Safe & Secure Traffic Control in Connected & Autonomous Vehicles |
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Kurztitel | TACTIFUL 2023 |
Land/Gebiet | Polen |
Ort | Kraków |
Zeitraum | 1/10/23 → 1/10/23 |
Internetadresse |
Fields of Expertise
- Information, Communication & Computing