ReMAV: Reward Modeling of Autonomous Vehicles for Finding Likely Failure Events
Autonomous vehicles are advanced driving systems that revolutionize transportation, but their vulnerability to adversarial attacks poses significant safety risks. Consider a scenario in which a slight perturbation in sensor data causes an autonomous vehicle to fail unexpectedly, potentially leading...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10714436/ |
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