Autonomous Vehicle Safety: An Interdisciplinary Challenge
Carnegie Mellon University · Edge Case Research (United States)
Abstract
Ensuring the safety of fully autonomous vehicles requires a multi-disciplinary approach across all the levels of functional hierarchy, from hardware fault tolerance, to resilient machine learning, to cooperating with humans driving conventional vehicles, to validating systems for operation in highly unstructured environments, to appropriate regulatory approaches. Significant open technical challenges include validating inductive learning in the face of novel environmental inputs and achieving the very high levels of dependability required for full-scale fleet deployment. However, the biggest challenge may be in creating an end-to-end design and deployment process that integrates the safety concerns of a myriad…
Citation impact
- FWCI
- 33.91
- Percentile
- 100%
- References
- 37
Authors
2Topics & keywords
- Software deployment
- Dependability
- Systems engineering
- Process (computing)
- Computer science
- Fault tolerance
- Risk analysis (engineering)
- Engineering