​Autonomous Vehicle Validation and Verification AV V&V testing produces multi-variate time series data as output, which is evaluated to determine testing coverage.
Project Details
Autonomous Vehicle Validation and Verification AV V&V testing produces multi-variate time series data as output, which is evaluated to determine testing coverage. The recent surge in interpretable Artificial Intelligence (AI) research has resulted in Python interfaces for modern interpretable AI implementations. In this project, various modern interpretable AI implementations will be applied to AV V&V testing data to interpret parameter impact, and generate an informative report of AV V&V scenario using data generated from a traffic simulator and AV V&V test scenarios.
Research Team
Principal Investigators
M. Ilhan Akbas
Associate Professor, Associate Chair, and Program Coord.
- Electrical Engineering and Computer Science Dept
- Daytona College of Engineering