1. [Publications](/publications) 2. ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection # ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection ![](/sites/default/files/styles/wide/public/pubs/2019-06_ML-based-Fault-Injection/default.jpg?itok=qHqsh6QA) The safety and resilience of fully autonomous vehicles (AVs) are of significant concern, as exemplified by several headline-making accidents. While AV development today involves verification, validation, and testing, end-to-end assessment of AV systems under accidental faults in realistic driving scenarios has been largely unexplored. This paper presents DriveFI, a machine learning-based fault injection engine, which can mine situations and faults that maximally impact AV safety, as demonstrated on two industry-grade AV technology stacks (from NVIDIA and Baidu). For example, DriveFI found 561 safety-critical faults in less than 4 hours. In comparison, random injection experiments executed over several weeks could not find any safety-critical faults. ## Authors Saurabh Jha (University of Illinois at Urbana-Champaign) Subho Banerjee (University of Illinois at Urbana-Champaign) Timothy Tsai (NVIDIA) [Siva Hari](/person/siva-hari) [Michael B. Sullivan](/person/mike-sullivan) Zbigniew T. Kalbarczyk (University of Illinois at Urbana-Champaign) [Steve Keckler](/person/stephen-keckler) Ravishankar K. Iyer (University of Illinois at Urbana-Champaign) ## Publication Date Monday, June 24, 2019 ## Published in [International Conference on Dependable Systems and Networks (DSN)](https://ieeexplore.ieee.org/abstract/document/8809495) ## Research Area [Artificial Intelligence and Machine Learning ](/research-area/machine-learning-artificial-intelligence) [Autonomous Vehicles](/research-area/autonomous-vehicles) [Resilience and Safety](/research-area/resilience) ## External Links [IEEE Digital Library](https://ieeexplore.ieee.org/abstract/document/8809495) ## Uploaded Files [Published manuscript](https://research.nvidia.com/sites/default/files/pubs/2019-06_ML-based-Fault-Injection//DSN2019-36-camera-ready.pdf "Open file in new window")3.25 MB ## Copyright This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to .