RGB cameras failures and their effects in autonomous driving applications
RGB cameras are one of the most relevant sensors for autonomous driving applications. It is undeniable that failures of vehicle cameras may compromise the autonomous driving task, possibly leading to unsafe behaviors when images that are subsequently processed by the driving system are altered. To support the definition of safe and robust vehicle architectures and intelligent systems, in this paper we define the failure modes of a vehicle camera, together with an analysis of effects and known mitigations. Further, we build a software library for the generation of the corresponding failed images and we feed them to six object detectors for mono and stereo cameras and to the self-driving agent of an autonomous driving simulator. The resulting misbehaviors with respect to operating with clean images allow a better understanding of failures effects and the related safety risks in image-based applications.
Code (1)
Tasks
Autonomous DrivingSimilar Papers 제목 키워드 기반
IGDrivSim: A Benchmark for the Imitation Gap in Autonomous Driving
Developing autonomous vehicles that can navigate complex environments with human-level safety and efficiency is a central goal in self-driving research. A common approach to achieving this is imitation learning, where ag…
Autonomous DrivingAutonomous VehiclesImitation LearningNavigateDeep Event-based Object Detection in Autonomous Driving: A Survey
Object detection plays a critical role in autonomous driving, where accurately and efficiently detecting objects in fast-moving scenes is crucial. Traditional frame-based cameras face challenges in balancing latency and …
Autonomous DrivingObjectobject-detectionObject DetectionDSEC: A Stereo Event Camera Dataset for Driving Scenarios
Once an academic venture, autonomous driving has received unparalleled corporate funding in the last decade. Still, the operating conditions of current autonomous cars are mostly restricted to ideal scenarios. This means…
Autonomous DrivingFusing Event-based and RGB camera for Robust Object Detection in Adverse Conditions
The ability to detect objects, under image corruptions and different weather conditions is vital for deep learning models especially when applied to real-world applications such as autonomous driving. Traditional RGB-bas…
3D Object DetectionAdversarial AttackAutonomous DrivingEvent-based vision+7Interpretable Safety Validation for Autonomous Vehicles
An open problem for autonomous driving is how to validate the safety of an autonomous vehicle in simulation. Automated testing procedures can find failures of an autonomous system but these failures may be difficult to i…
Autonomous DrivingAutonomous Vehicles