Efficient and Effective Generation of Test Cases for Pedestrian Detection - Search-based Software Testing of Baidu Apollo in SVL

@article{Ebabi2021EfficientAE,
  title={Efficient and Effective Generation of Test Cases for Pedestrian Detection - Search-based Software Testing of Baidu Apollo in SVL},
  author={Hamid Ebabi and Mahshid Helali Moghadam and Markus Borg and Gregory Gay and Afonso Fontes and Kasper Socha},
  journal={2021 IEEE International Conference on Artificial Intelligence Testing (AITest)},
  year={2021},
  pages={103-110}
}
With the growing capabilities of autonomous vehicles, there is a higher demand for sophisticated and pragmatic quality assurance approaches for machine learning-enabled systems in the automotive AI context. The use of simulation-based prototyping platforms provides the possibility for early-stage testing, enabling inexpensive testing and the ability to capture critical corner-case test scenarios. Simulation-based testing properly complements conventional on-road testing. However, due to the… Expand

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