scenarioxp

scenarioxp is a toolkit which implements various strategies for sampling concrete parameters from logical scenarios with parameter ranges which is scalable to any number of dimensions. This module extends our other toolkit sim_bug_tools, exploiting it's utility in a way that is intuitive and effective while conforming to common datascience data structures of Python.

This module is developed for research in scenario-based testing for the validation and verification (V&V) of autonomous vehicles (AV). We were frustrated by the limitations imposed by time and resource cost of the AV V&V testing process given the many configurations of parameters for AV Testing. This module contains the tools we use to understand and navigate these high-dimensional spaces.

Authors

This module is produced as a product of PhD dissertation research by the authors at Embry-Riddle Aeronautical University of Daytona Beach, Florida. Dept. of Electrical Engineering and Computer Science.

PhD Advisor
Dr. Mustafa Ilhan Akbas akbasm@erau.edu

PhD Student
Quentin Goss gossq@my.erau.edu

Citing This Work

If you would like to cite this work. Pleace cite our latest paper about the topic.

Q. Goss, W. C. Pate, and M. I. Akbas ̧, “An Integrated Scenario-Based Testing and Explanation Framework for Autonomous Vehicles,” accepted to 2024 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST), IEEE.